Characterization and application of aptamers for Taq DNA polymerase selected using an evolution-mimicking algorithm

Using an evolution-mimicking algorithm (EMA), we have recently identified DNA aptamers that inhibit Taq DNA polymerase. In the present study, we have attempted to improve further the inhibitory activities of aptamers, as well as to characterize those aptamers with the most potent inhibitory activities. To characterize the most potent aptamer and demonstrate its applicability, the abilities to inhibit Tth DNA polymerase and to modulate specific amplification in PCR were investigated. This aptamer inhibited both Tth DNA polymerase and Taq DNA polymerase and improved the specificity of detection of a low-copy-number target gene in PCR using these DNA polymerases.     

Analysis of the evolution of the thrombin-inhibiting DNA aptamers using a genetic algorithm

We previously identified a thrombin-inhibiting DNA aptamer that was presumed to form a G-quartet structure with a duplex. To investigate the importance of the sequences in the duplex region and to obtain aptamers with higher inhibitory activities, we randomized the sequences of the duplex region of this aptamer and carried out selection based on inhibitory activity using a genetic algorithm. This method consisted of selection via an inhibition assay, crossover, and mutation in silico. After two cycles, we obtained ligands with greater inhibitory activities than that of the original aptamer. In addition, the duplex sequences were found to contribute to the inhibitory activities of aptamers.     

A novel method of identifying genetic mutations using an electrochemical DNA array

We describe the development of a new type of DNA array chip that utilizes electrochemical reactions and a novel method of simultaneously identifying multiple genetic mutations on an array chip. The electrochemical array (ECA) uses a threading intercalator specific to double-stranded nucleotides, ferrocenylnaphthalene diimide (FND), as the indicator. ECA does not require target labeling, and the equipment is simple, durable and less expensive. The simultaneous multiple mutation detection (SMMD) system using an ECA chip and FND utilizes an enzyme to simultaneously distinguish several genetic mutations such as single nucleotide polymorphism (SNP), insertion, deletion, translocation and short tandem repeat. We examined this SMMD system using an ECA chip, by detecting seven different mutations on the lipoprotein lipase (LPL) gene for 50 patients in a blind test. It turned out that all the results obtained were concordant with the sequencing results, demonstrating that this system is a powerful tool for clinical applications.     

Selection of DNA aptamers using atomic force microscopy

Atomic force microscopy (AFM) can detect the adhesion or affinity force between a sample surface and cantilever, dynamically. This feature is useful as a method for the selection of aptamers that bind to their targets with very high affinity. Therefore, we propose the Systematic Evolution of Ligands by an EXponential enrichment (SELEX) method using AFM to obtain aptamers that have a strong affinity for target molecules. In this study, thrombin was chosen as the target molecule, and an ‘AFM-SELEX’ cycle was performed. As a result, selected cycles were completed with only three rounds, and many of the obtained aptamers had a higher affinity to thrombin than the conventional thrombin aptamer. Moreover, one type of obtained aptamer had a high affinity to thrombin as well as the anti-thrombin antibody. AFM-SELEX is, therefore, considered to be an available method for the selection of DNA aptamers that have a high affinity for their target molecules.     

Deconvolution of a complex target using DNA aptamers

In vitro selection of single-stranded nucleic acid aptamers from large random sequence libraries is now a straightforward process particularly when screening with a single target molecule. These libraries contain considerable shape diversity as evident by the successful isolation of aptamers that bind with high affinity and specificity to chemically diverse targets. We propose that aptamer libraries contain sufficient shape diversity to allow deconvolution of a complex mixture of targets. Using unfractionated human plasma as our experimental model, we aim to develop methods to obtain aptamers against as many proteins as possible. To begin, it is critical that we understand how aptamer populations change with increasing rounds of in vitro selection when using complex mixtures. Our results show that sequence representation in the selected population changes dramatically with increasing rounds of selection. Certain aptamer families were apparent after only three selection rounds. Two additional cycles saw a decline in the relative abundance of these families and the emergence of yet another family that accounted for more than 60% of sequences in the pool. To overcome this population convergence, an aptamer-based target depletion method was developed, and the library screen was repeated. The previous dominant family effectively disappeared from the selected populations but was replaced by other aptamer families. Insights gained from these initial experiments are now being applied in the creation of second generation plasma protein screens and also to the analysis of other complex biological targets.     

A novel screening method of cellulase-producing bacteria

Cellulase is the key to utilize the renewable and abundant cellulose resource, cellulase-producing microorganism is an important source of cellulase. The traditional screening method of cellulase-producing microorganism is low efficacy and not macroscopic. The screening method in this study was based on the interactive culture character between cellulase-producing bacteria and Phytophthora parasitica var. nicotianae on plates, the results indicated that the inhibition zone and cellulase activity of bacterial strains are conformity on the whole, so the screening method is very quickly and apparent.     

High-throughput quantitative binding analysis of DNA aptamers using exonucleases

Aptamers are nucleic acid bioreceptors that have been used in various applications including medical diagnostics and as therapeutic agents. Identifying the most optimal aptamer for a particular application is very challenging. Here, we for the first time have developed a high-throughput method for accurately quantifying aptamer binding affinity, specificity, and cross-reactivity via the kinetics of aptamer digestion by exonucleases. We demonstrate the utility of this approach by isolating a set of new aptamers for fentanyl and its analogs, and then characterizing the binding properties of 655 aptamer–ligand pairs using our exonuclease digestion assay and validating the results with gold-standard methodologies. These data were used to select optimal aptamers for the development of new sensors that detect fentanyl and its analogs in different analytical contexts. Our approach dramatically accelerates the aptamer characterization process and streamlines sensor development, and if coupled with robotics, could enable high-throughput quantitative analysis of thousands of aptamer–ligand pairs.     

Semi-automated selection of DNA aptamers using magnetic particle handling

We have developed a semi-automatic selection procedure for DNA aptamers. Employing a robotic workstation for magnetic particle handling, this method allows for a fast, reproducible, and parallelized selection of DNA aptamers. The selection protocol is designed to provide high flexibility and versatility in terms of choice of buffers and reagents, as well as stringency of selection. Using this procedure, we have successfully isolated ligand-specific, high-affinity DNA aptamers.     

A novel and simple method of screening compounds for interaction with DNA: A validation study

We report the development of a simple, cost-effective assay for detecting compounds that have the ability to interact with and modify DNA. Potential uses for the assay lie in the areas of early genotoxicity testing of drug candidates, anticancer and antibiotic drug discovery, environmental monitoring and testing in the food, beverage and cosmetics industries. At present the assay has been used to assess direct-acting compounds only and it is yet to be established whether the assay is compatible with bio-activation. The methodology is based on the oxidative reaction of potassium permanganate with pyrimidine bases, which have become perturbed and more reactive by the agent under test. Results are recorded by use of UV/vis spectroscopy. The adaptation to a multi-well plate format provides the capacity for high throughput utilizing small amounts of compounds. Over 100 compounds, comprising different classes of DNA-binding chemicals as well as non-binding controls, have been put through the assay and the results compared with existing genotoxicity testing data from other methods. The assay has shown to be predictive of the results of other genotoxicity testing methods. We have found that the method is overall predictive of 71% of Ames bacterial reverse-mutation test results (where data are given) encompassing both negative and positive results.     

DNA aptamers against the Lup an 1 food allergen

Using in vitro selection, high affinity DNA aptamers to the food allergen Lup an 1, ß-conglutin, were selected from a pool of DNA, 93 bases in length, containing a randomised sequence of 49 bases. ß-conglutin was purified from lupin flour and chemically crosslinked to carboxylated magnetic beads. Peptide mass fingerprinting was used to confirm the presence of the ß-conglutin. Single stranded DNA was generated from the randomised pool using T7 Gene 6 Exonuclease and was subsequently incubated with the magnetic beads and the captured DNA was released and amplified prior to a further round of Systematic Evolution of Ligands by Exponential Enrichment (SELEX). Evolution was monitored using enzyme linked oligonucleotide assay and surface plasmon resonance. Once a plateau in evolution was reached, the isolated DNA sequences were cloned and sequenced. The consensus motif was identified via alignment of the sequences and the affinities of these sequences for immobilised ß-conglutin were determined using surface plasmon resonance. The selected aptamer was demonstrated to be highly specific, showing no cross-reactivity with other flour ingredients or with other conglutin fractions of lupin. The secondary structures of the selected aptamers were predicted using m-fold. Finally, the functionality of the selected aptamers was demonstrated using a competitive assay for the quantitative detection of ß-conglutin. . Future work will focus on structure elucidation and truncation of the selected sequences to generate a smaller aptamer for application to the analysis of the Lup an 1 allergen in foodstuffs.     

A simple and direct electrochemical detection of interferon-gamma using its RNA and DNA aptamers

Tuberculosis is the most frequent cause of infection-related death worldwide. We constructed a simple and direct electrochemical sensor to detect interferon (IFN)-gamma, a selective marker for tuberculosis pleurisy, using its RNA and DNA aptamers. IFN-gamma was detected by its 5'-thiol-modified aptamer probe immobilized on the gold electrode. Interaction between IFN-gamma and the aptamer was recorded using electrochemical impedance spectroscopy and quartz crystal microbalance (QCM) with high sensitivity. The RNA-aptamer-based sensor showed a low detection limit of 100 fM, and the DNA-aptamer-based sensor detected IFN-gamma to 1 pM in sodium phosphate buffer. With QCM analysis, the aptamer immobilized on the electrode and IFN-gamma bound to the aptamer probe was quantified. This QCM result shows that IFN-gamma exists in multimeric forms to interact with the aptamers, and the RNA aptamer prefers the high multimeric state of IFN-gamma. Such a preference may describe the low detection limit of the RNA aptamer shown by impedance analysis. In addition, IFN-gamma was detected to 10 pM by the DNA aptamer in fetal bovine serum, a mimicked biological system, which has similar components to pleural fluid.     

A diabetic retinopathy detection method using an improved pillar K-means algorithm

The paper presents a new approach for medical image segmentation. Exudates are a visible sign of diabetic retinopathy that is the major reason of vision loss in patients with diabetes. If the exudates extend into the macular area, blindness may occur. Automated detection of exudates will assist ophthalmologists in early diagnosis. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after getting optimized by Pillar algorithm; pillars are constructed in such a way that they can withstand the pressure. Improved pillar algorithm can optimize the K-means clustering for image segmentation in aspects of precision and computation time. This evaluates the proposed approach for image segmentation by comparing with Kmeans and Fuzzy C-means in a medical image. Using this method, identification of dark spot in the retina becomes easier and the proposed algorithm is applied on diabetic retinal images of all stages to identify hard and soft exudates, where the existing pillar K-means is more appropriate for brain MRI images. This proposed system help the doctors to identify the problem in the early stage and can suggest a better drug for preventing further retinal damage.     

A novel screening method to assess developability of antibody-like molecules

Monoclonal antibodies and antibody-like molecules represent a fast-growing class of bio-therapeutics that has rapidly transformed patient care in a variety of disease indications. The discovery of antibodies that bind to particular targets with high affinity is now a routine exercise and a variety of in vitro and in vivo techniques are available for this purpose. However, it is still challenging to identify antibodies that, in addition to having the desired biological effect, also express well, remain soluble at different pH levels, remain stable at high concentrations, can withstand high shear stress, and have minimal non-specific interactions. Many promising antibody programs have ultimately failed in development due to the problems associated with one of these factors. Here, we present a simple high-performance liquid chromatography (HPLC)-based screening method to assess these developability factors earlier in discovery process. This method is robust and requires only microgram quantities of proteins. Briefly, we show that for antibodies injected on a commercially available pre-packed Zenix HPLC column, the retention times are inversely related to their colloidal stability with antibodies prone to precipitation or aggregation retained longer on the column with broader peaks. By simply varying the salt content of running buffer, we were also able to estimate the nature of interactions between the antibodies and the column. We believe this approach should generally be applicable to assessment of the developability of other classes of bio-therapeutic molecules, and that the addition of this simple tool early in the discovery process will lead to selection of molecules with improved developability characteristics.     

A novel artificial intelligence-based approach for identification of deoxynucleotide aptamers

The selection of a DNA aptamer through the Systematic Evolution of Ligands by EXponential enrichment (SELEX) method involves multiple binding steps, in which a target and a library of randomized DNA sequences are mixed for selection of a single, nucleotide-specific molecule. Usually, 10 to 20 steps are required for SELEX to be completed. Throughout this process it is necessary to discriminate between true DNA aptamers and unspecified DNA-binding sequences. Thus, a novel machine learning-based approach was developed to support and simplify the early steps of the SELEX process, to help discriminate binding between DNA aptamers from those unspecified targets of DNA-binding sequences. An Artificial Intelligence (AI) approach to identify aptamers were implemented based on Natural Language Processing (NLP) and Machine Learning (ML). NLP method (CountVectorizer) was used to extract information from the nucleotide sequences. Four ML algorithms (Logistic Regression, Decision Tree, Gaussian Naïve Bayes, Support Vector Machines) were trained using data from the NLP method along with sequence information. The best performing model was Support Vector Machines because it had the best ability to discriminate between positive and negative classes. In our model, an Accuracy (A) of 0.995, the fraction of samples that the model correctly classified, and an Area Under the Receiving Operating Curve (AUROC) of 0.998, the degree by which a model is capable of distinguishing between classes, were observed. The developed AI approach is useful to identify potential DNA aptamers to reduce the amount of rounds in a SELEX selection. This new approach could be applied in the design of DNA libraries and result in a more efficient and faster process for DNA aptamers to be chosen during SELEX.     

A novel method for DNA molecular counting.

We have developed a new method for counting DNA molecules using 'capillary-plates' consisting of a large number of small glass-capillary 'channels' fused together in parallel. PCR mixtures containing serially diluted DNA templates with the DNA indicator dye Hoechst 33258 were poured into the plates and sealed with silicone rubber-plates. Following 40 PCR cycles, fluorescence microscopy revealed that the fluorescence in some channels had increased about three-times more than in others at template concentrations of 1 fM or lower. No bright fluorescence was observed in the absence of template. The relationship between the proportion of fluorescent channels in the capillary-plates and the template concentrations was linear according to Poisson probabilities in the range of 0.1-1,000 aM. These results demonstrate the amplification of single templates in the channels, and that a small number of templates could be quantified by counting the proportion of positive channels on the capillary-plates.     

A method to select chemically modified aptamers directly

In vitro selection is a strategy to identify high-affinity ligands of a predetermined target among a large pool of randomized oligonucleotides. Most in vitro selections are performed with unmodified RNA or DNA sequences, leading to ligands of high affinity and specificity (aptamers) but of very short lifetime in the ex vivo and in vivo context. Only a very limited number of modified triphosphate nucleotides conferring nuclease resistance to the oligomer can be incorporated by polymerases. This encourages the development of alternative methods for the identification of nuclease-resistant aptamers. In this paper, we describe such a method. After selection of 2'O-methyl oligonucleotides against the TAR RNA structure of HIV-1, the complementary DNA sequences are fished out of a pool of randomized oligodeoxynucleotides by Watson-Crick hybridization. The DNA-fished sequences are amplified by PCR as double and single strands, the latter being used to fish back the chemically modified candidates from the initial library. This procedure allows an indirect amplification of the selected candidates. This enriched pool of modified sequences is then used for the next selection round against the target.     

Parallel production and verification of protein products using a novel high-throughput screening method

Protein production and analysis in a parallel fashion is today applied in laboratories worldwide and there is a great need to improve the techniques and systems used for this purpose. In order to save time and money, a fast and reliable screening method for analysis of protein production and also verification of the protein product is desired. Here, a micro-scale protocol for the parallel production and screening of 96 proteins in plate format is described. Protein capture was achieved using immobilized metal affinity chromatography and the product was verified using matrix-assisted laser desorption ionization time-of-flight MS. In order to obtain sufficiently high cell densities and product yield in the small-volume cultivations, the EnBase® cultivation technology was applied, which enables cultivation in as small volumes as 150 μL. Here, the efficiency of the method is demonstrated by producing 96 human, recombinant proteins, both in micro-scale and using a standard full-scale protocol and comparing the results in regard to both protein identity and sample purity. The results obtained are highly comparable to those acquired through employing standard full-scale purification protocols, thus validating this method as a successful initial screening step before protein production at a larger scale.