AptCompare: optimized de novo motif discovery of RNA aptamers via HTS-SELEX

Truncation-Enhanced Aptamer Binding Affinity and Its Potential as a Sensor for Macrobrachium rosenbergii Nodavirus Detection

White tail disease in Macrobrachium rosenbergii is caused by M. rosenbergii nodavirus (MrNV) infection, resulting in up to 100% mortality in larvae and post-larvae stages, severely impacting aquaculture production. Existing genome-based detection methods for MrNV are costly and time-consuming, highlighting the need for rapid and cost-effective diagnostic tests. This study evaluated the effects of truncating selected aptamer on its binding affinity to the MrNV capsid protein. The previously isolated and identified aptamer through magnetic-capture SELEX and Next Generation Sequencing demonstrated high binding affinity to the MrNV capsid protein. Truncation at the primer overhang was found to improve binding affinity, reducing the dissociation constant from 347 nM to 30.1 nM. The calculated limit of detection for the truncated aptamer decreased from 5.64 nM to 1.7 nM, while the limit of quantification decreased from 17.1 nM to 5.16 nM. These reductions indicate that the truncated aptamer has higher sensitivity compared to the full-length aptamer. In tests with MrNV-infected M. rosenbergii samples, both the enzyme-linked aptamer assay and the gold nanoparticle aptasensor assay showed consistent results when 0.5 μg of total protein lysate was used. This indicates that the prawn protein concentration interferes with the detection of the viral protein. These findings suggest the potential application of the truncated aptamer as a sensor in the development of a practical aptamer-based diagnostic kit. For instance, an aptamer-based lateral flow assay test kit could provide a user-friendly, cost-effective solution that eliminates the need for sophisticated instrumentation for diagnosis or data interpretation, making it ideal for detecting MrNV infection in M. rosenbergii aquaculture.

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative systematic evolution of ligands by exponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Here we present AptamerRunner, an aptamer sequence and/or structure clustering algorithm that synergistically integrates computational analysis with visualization and expertise-directed decision making. The visual integration of networked aptamers with ranking data, such as fold enrichment or scoring algorithm results, represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner have broad-reaching implications for aptamer researchers across a wide range of disciplines.

Prediction of aptamer affinity using an artificial intelligence approach

Aptamers are oligonucleotide sequences that can connect to particular target molecules, similar to monoclonal antibodies. They can be chosen by systematic evolution of ligands by exponential enrichment (SELEX), and are modifiable and can be synthesized. Even if the SELEX approach has been improved a lot, it is frequently challenging and time-consuming to identify aptamers experimentally. In particular, structure-based methods are the most used in computer-aided design and development of aptamers. For this purpose, numerous web-based platforms have been suggested for the purpose of forecasting the secondary structure and 3D configurations of RNAs and DNAs. Also, molecular docking and molecular dynamics (MD), which are commonly utilized in protein compound selection by structural information, are suitable for aptamer selection. On the other hand, from a large number of sequences, artificial intelligence (AI) may be able to quickly discover the possible aptamer candidates. Conversely, sophisticated machine and deep-learning (DL) models have demonstrated efficacy in forecasting the binding properties between ligands and targets during drug discovery; as such, they may provide a reliable and precise method for forecasting the binding of aptamers to targets. This research looks at advancements in AI pipelines and strategies for aptamer binding ability prediction, such as machine and deep learning, as well as structure-based approaches, molecular dynamics and molecular docking simulation methods.

Current developments of SELEX technologies and prospects in the aptamer selection with clinical applications

Aptamers are single-stranded oligonucleotide sequences capable of binding to specific ligands with high affinity. In this manner, they are like antibodies but have advantages such as lower manufacturing costs, lower immunogenicity, fewer batch-to-batch differences, a longer shelf life, high tolerance to different molecular milieus, and a greater number of potential targets. Due to their special features, they have been used in drug delivery, biosensor technology, therapy, and diagnostics. The methodology that allowed its production was the "Systematic Evolution of Ligands by Exponential enrichment" (SELEX). Unfortunately, the traditional protocol is time-consuming and laborious. Therefore, numerous variants with considerable optimization steps have been developed, nonetheless, there are still challenges to achieving real applications in the clinical field. Among them, are control of in vivo activities, fast renal filtration, degradation by nucleases and toxicity testing. This review focuses on current technologies based on SELEX, the critical factors for successful aptamer selection, and its upcoming biomedical and biotechnological applications.

Aptamers as an approach to targeted cancer therapy

Conventional cancer treatments can cause serious side effects because they are not specific to cancer cells and can damage healthy cells. Aptamers often are single-stranded oligonucleotides arranged in a unique architecture, allowing them to bind specifically to target sites. This feature makes them an ideal choice for targeted therapeutics. They are typically produced through the systematic evolution of ligands by exponential enrichment (SELEX) and undergo extensive pharmacological revision to modify their affinity, specificity, and therapeutic half-life. Aptamers can act as drugs themselves, directly inhibiting tumor cells. Alternatively, they can be used in targeted drug delivery systems to transport drugs directly to tumor cells, minimizing toxicity to healthy cells. In this review, we will discuss the latest and most advanced approaches to using aptamers for cancer treatment, particularly targeted therapy overcoming resistance to conventional therapies.

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer clustering algorithm that generates visual networks of aptamers that are related by sequence and/or structure. These networks can then be overlayed with ranking data, such as fold enrichment or data from scoring algorithms. The ability to visually integrate data using AptamerRunner represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines.

Electrochemical aptasensors for pathogenic detection toward point-of-care diagnostics

A biosensor system refers to a biomedical device, which detects biological, chemical, or biochemical components by converting those signals to an electrical signal by utilizing and uniting physical or chemical transducer with biorecognition elements. An electrochemical biosensor is generally based on the reaction of either production or consumption of electrons under a three-electrode system. Biosensor systems are exploited in a wide range of areas, such as medicine, agriculture, husbandry, food, industry, environment protection, quality control, waste disposal, and the military. Pathogenic infections are the third leading cause of death worldwide after cardiovascular diseases and cancer. Therefore, there is an urgent need for effective diagnostic tools to control food, water, and soil contamination result in protecting human life and health. Aptamers are peptide or oligonucleotide-based molecules that show very high affinity to their targets that are produced from large pools of random amino acid or oligonucleotide sequences. Generally, aptamers have been utilized for fundamental sciences and clinical implementations for their target-specific affinity and have been intensely exploited for different kinds of biosensor applications for approximately 30 years. The convergence of aptamers with biosensor systems enabled the construction of voltammetric, amperometric, and impedimetric biosensors for the detection of specific pathogens. In this review, electrochemical aptamer biosensors were evaluated by discussing the definition, types, and production techniques of aptamers, the advantages of aptamers as a biological recognition element against their alternatives, and a wide range of aptasensor examples from literature in the detection of specific pathogens.

In vitro selection of aptamers and their applications

The introduction of the in-vitro evolution method known as SELEX (Systematic Evolution of Ligands by Exponential enrichment) more than 30 years ago led to the conception of versatile synthetic receptors known as aptamers. Offering many benefits such as low cost, high stability and flexibility, aptamers have sparked innovation in molecular diagnostics, enabled advances in synthetic biology and have facilitated new therapeutic approaches. The SELEX method itself is inherently adaptable and offers near limitless possibilities in yielding functional nucleic acid ligands. This Primer serves to provide guidance on experimental design and highlight new growth areas for this impactful technology.

Design and Prediction of Aptamers Assisted by In Silico Methods

An aptamer is a single-stranded DNA or RNA that binds to a specific target with high binding affinity. Aptamers are developed through the process of systematic evolution of ligands by exponential enrichment (SELEX), which is repeated to increase the binding power and specificity. However, the SELEX process is time-consuming, and the characterization of aptamer candidates selected through it requires additional effort. Here, we describe in silico methods in order to suggest the most efficient way to develop aptamers and minimize the laborious effort required to screen and optimise aptamers. We investigated several methods for the estimation of aptamer-target molecule binding through conformational structure prediction, molecular docking, and molecular dynamic simulation. In addition, examples of machine learning and deep learning technologies used to predict the binding of targets and ligands in the development of new drugs are introduced. This review will be helpful in the development and application of in silico aptamer screening and characterization.

Target-switch SELEX: Screening with alternating targets to generate aptamers to conserved terminal dipeptides

Systematic evolution of ligands by exponential enrichment (SELEX) encompasses a wide variety of high-throughput screening techniques for producing nucleic acid binders to molecular targets through directed evolution. We describe here the design and selection steps for discovery of DNA aptamers with specificity for the two consecutive N-terminal amino acids (AAs) of a small peptide (8-10 amino acids). This bead-based method may be adapted for applications requiring binders which recognize a specific portion of the desired target. For complete details on the use and execution of this protocol, please refer to Hong et al. (2022).

FASTAptameR 2.0: A web tool for combinatorial sequence selections

Combinatorial selections are powerful strategies for identifying biopolymers with specific biological, biomedical, or chemical characteristics. Unfortunately, most available software tools for high-throughput sequencing analysis have high entrance barriers for many users because they require extensive programming expertise. FASTAptameR 2.0 is an R-based reimplementation of FASTAptamer designed to minimize this barrier while maintaining the ability to answer complex sequence-level and population-level questions. This open-source toolkit features a user-friendly web tool, interactive graphics, up to 100 times faster clustering, an expanded module set, and an extensive user guide. FASTAptameR 2.0 accepts diverse input polymer types and can be applied to any sequence-encoded selection.

Electrochemical Aptasensors for Antibiotics Detection: Recent Achievements and Applications for Monitoring Food Safety

Antibiotics are often used in human and veterinary medicine for the treatment of bacterial diseases. However, extensive use of antibiotics in agriculture can result in the contamination of common food staples such as milk. Consumption of contaminated products can cause serious illness and a rise in antibiotic resistance. Conventional methods of antibiotics detection such are microbiological assays chromatographic and mass spectroscopy methods are sensitive; however, they require qualified personnel, expensive instruments, and sample pretreatment. Biosensor technology can overcome these drawbacks. This review is focused on the recent achievements in the electrochemical biosensors based on nucleic acid aptamers for antibiotic detection. A brief explanation of conventional methods of antibiotic detection is also provided. The methods of the aptamer selection are explained, together with the approach used for the improvement of aptamer affinity by post-SELEX modification and computer modeling. The substantial focus of this review is on the explanation of the principles of the electrochemical detection of antibiotics by aptasensors and on recent achievements in the development of electrochemical aptasensors. The current trends and problems in practical applications of aptasensors are also discussed.

Implementation of High-Throughput Sequencing (HTS) in Aptamer Selection Technology

Aptamers are nucleic acid ligands that bind specifically to a target of interest. Aptamers have gained in popularity due to their high potential for different applications in analysis, diagnostics, and therapeutics. The procedure called systematic evolution of ligands by exponential enrichment (SELEX) is used for aptamer isolation from large nucleic acid combinatorial libraries. The huge number of unique sequences implemented in the in vitro evolution in the SELEX process imposes the necessity of performing extensive sequencing of the selected nucleic acid pools. High-throughput sequencing (HTS) meets this demand of SELEX. Analysis of the data obtained from sequencing of the libraries produced during and after aptamer isolation provides an informative basis for precise aptamer identification and for examining the structure and function of nucleic acid ligands. This review discusses the technical aspects and the potential of the integration of HTS with SELEX.