FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections

Nuclease-assisted selection of slow-off rate aptamers

Conventional directed evolution methods offer the ability to select bioreceptors with high binding affinity for a specific target in terms of thermodynamic properties. However, there is a lack of analogous approaches for kinetic selection, which could yield affinity reagents that exhibit slow off-rates and thus remain tightly bound to targets for extended periods. Here, we describe an in vitro directed evolution methodology that uses the nuclease flap endonuclease 1 to achieve the efficient discovery of aptamers that have slow dissociation rates. Our nuclease-assisted selection strategy can yield specific aptamers for both small molecules and proteins with off-rates that are an order of magnitude slower relative to those obtained with conventional selection methods while still retaining excellent overall target affinity in terms of thermodynamics. This new methodology provides a generalizable approach for generating slow off-rate aptamers for diverse targets, which could, in turn, prove valuable for applications including molecular devices, bioimaging, and therapy.

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities

The integration of artificial intelligence (AI) into point-of-care (POC) biosensing has the potential to revolutionize diagnostic methodologies by offering rapid, accurate, and accessible health assessment directly at the patient level. This review paper explores the transformative impact of AI technologies on POC biosensing, emphasizing recent computational advancements, ongoing challenges, and future prospects in the field. We provide an overview of core biosensing technologies and their use at the POC, highlighting ongoing issues and challenges that may be solved with AI. We follow with an overview of AI methodologies that can be applied to biosensing, including machine learning algorithms, neural networks, and data processing frameworks that facilitate real-time analytical decision-making. We explore the applications of AI at each stage of the biosensor development process, highlighting the diverse opportunities beyond simple data analysis procedures. We include a thorough analysis of outstanding challenges in the field of AI-assisted biosensing, focusing on the technical and ethical challenges regarding the widespread adoption of these technologies, such as data security, algorithmic bias, and regulatory compliance. Through this review, we aim to emphasize the role of AI in advancing POC biosensing and inform researchers, clinicians, and policymakers about the potential of these technologies in reshaping global healthcare landscapes.

Genome-wide CRISPR/Cas9 screen reveals JunB downmodulation of HIV co-receptor CXCR4

HIV-1 relies extensively on host cell machinery for replication. Identification and characterization of these host-virus interactions is vital to our understanding of viral replication and the consequences of infection in cells. Several prior screens have identified host factors important for HIV replication but with limited replication of findings, likely due to differences in experimental design and conditions. Thus, unidentified factors likely exist. To identify novel host factors required for HIV-1 infection, we performed a genome-wide CRISPR/Cas9 screen using HIV-induced cell death as a partitioning method. We created a gene knockout library in TZM-GFP reporter cells using GeCKOv2, which targets 19,050 genes, and infected the library with a lethal dose of HIV-1NL4-3. We hypothesized that cells with a knockout of a gene critical for HIV infection would survive while cells with a knockout of a non-consequential gene would undergo HIV-induced death and be lost from the population. Surviving cells were analyzed by high throughput sequencing of the integrated CRISPR/Cas9 cassette to identify the gene knockout. Of the gene targets, an overwhelming majority of the surviving cells harbored the guide sequence for the AP-1 transcription factor family protein, JunB. Upon the generation of a clonal JunB knockout cell line, we found that HIV-1NL4-3 infection was blocked in the absence of JunB. The phenotype resulted from downregulation of CXCR4, as infection levels were recovered by reintroduction of CXCR4 in JunB KO cells. Thus, JunB downmodulates CXCR4 expression in TZM-GFP cells, reducing CXCR4-tropic HIV infection.

Developing Aptamer-Based Colorimetric Opioid Tests

Opioids collectively cause over 80,000 deaths in the United States annually. The ability to rapidly identify these compounds in seized drug samples on-site will be essential for curtailing trafficking and distribution. Chemical reagent-based tests are fast and simple but also notorious for giving false results due to poor specificity, whereas portable Raman spectrometers have excellent selectivity but often face interference challenges with impure drug samples. In this work, we develop on-site sensors for morphine and structurally related opioid compounds based on in vitro-selected oligonucleotide affinity reagents known as aptamers. We employ a parallel-and-serial selection strategy to isolate aptamers that recognize heroin, morphine, codeine, hydrocodone, and hydromorphone, along with a toggle-selection approach to isolate aptamers that bind oxycodone and oxymorphone. We then utilize a new high-throughput sequencing-based approach to examine aptamer growth patterns over the course of selection and a high-throughput exonuclease-based screening assay to identify optimal aptamer candidates. Finally, we use two high-performance aptamers with KD of ∼1 μM to develop colorimetric dye-displacement assays that can specifically detect opioids like heroin and oxycodone at concentrations as low as 0.5 μM with a linear range of 0-16 μM. Importantly, our assays can detect opioids in complex chemical matrices, including pharmaceutical tablets and drug mixtures; in contrast, the conventional Marquis test completely fails in this context. These aptamer-based colorimetric assays enable the naked-eye identification of specific opioids within seconds and will play an important role in combatting opioid abuse.

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.

High-Affinity Aptamers for In Vitro and In Vivo Cocaine Sensing

The ability to quantify cocaine in biological fluids is crucial for both the diagnosis of intoxication and overdose in the clinic as well as investigation of the drug's pharmacological and toxicological effects in the laboratory. To this end, we have performed high-stringency in vitro selection to generate DNA aptamers that bind cocaine with nanomolar affinity and clinically relevant specificity, thus representing a dramatic improvement over the current-generation, micromolar-affinity, low-specificity cocaine aptamers. Using these novel aptamers, we then developed two sensors for cocaine detection. The first, an in vitro fluorescent sensor, successfully detects cocaine at clinically relevant levels in 50% human serum without responding significantly to other drugs of abuse, endogenous substances, or a diverse range of therapeutic agents. The second, an electrochemical aptamer-based sensor, supports the real-time, seconds-resolved measurement of cocaine concentrations in vivo in the circulation of live animals. We believe the aptamers and sensors developed here could prove valuable for both point-of-care and on-site clinical cocaine detection as well as fundamental studies of cocaine neuropharmacology.

Diagnostic and Therapeutic Aptamers: A Promising Pathway to Improved Cardiovascular Disease Management

Despite advances in care, cardiovascular diseases remain the leading cause of death worldwide. As a result, identifying suitable biomarkers for early diagnosis and improving therapeutic and diagnostic strategies is crucial. Because of their significant advantages over other therapeutic approaches, nucleic-based therapies, particularly aptamers, are gaining increased attention. Aptamers are innovative synthetic polymers or oligomers of single-stranded DNA (ssDNA) or RNA molecules that can form 3-dimensional structures and thus interact with their targets with high specificity and affinity. Furthermore, they outperform classical protein-based antibodies in terms of in vitro selection, production, ease of modification and conjugation, high stability, low immunogenicity, and suitability for nanoparticle functionalization for targeted drug delivery. This work aims to review the advances made in the aptamers' field in biomarker detection, diagnosis, imaging, and targeted therapy, which highlight their huge potential in the management of cardiovascular diseases.

De Novo Single-Stranded RNA-Binding Peptides Discovered by Codon-Restricted mRNA Display

RNA-binding proteins participate in diverse cellular processes, including DNA repair, post-transcriptional modification, and cancer progression through their interactions with RNAs, making them attractive for biotechnological applications. While nature provides an array of naturally occurring RNA-binding proteins, developing de novo RNA-binding peptides remains challenging. In particular, tailoring peptides to target single-stranded RNA with low complexity is difficult due to the inherent structural flexibility of RNA molecules. Here, we developed a codon-restricted mRNA display and identified multiple de novo peptides from a peptide library that bind to poly(C) and poly(A) RNA with KDs ranging from micromolar to submicromolar concentrations. One of the newly identified peptides is capable of binding to the cytosine-rich sequences of the oncogenic Cdk6 3'UTR RNA and MYU lncRNA, with affinity comparable to that of the endogenous binding protein. Hence, we present a novel platform for discovering de novo single-stranded RNA-binding peptides that offer promising avenues for regulating RNA functions.

Post-transcriptional capping generates coenzyme A-linked RNA

NAD can be inserted co-transcriptionally via non-canonical initiation to form NAD-RNA. However, that mechanism is unlikely for CoA-linked RNAs due to low intracellular concentration of the required initiator nucleotide, 3'-dephospho-CoA (dpCoA). We report here that phosphopantetheine adenylyltransferase (PPAT), an enzyme of CoA biosynthetic pathway, accepts RNA transcripts as its acceptor substrate and transfers 4'-phosphopantetheine to yield CoA-RNA post-transcriptionally. Synthetic natural (RNAI) and small artificial RNAs were used to identify the features of RNA that are needed for it to serve as PPAT substrate. RNAs with 4-10 unpaired nucleotides at the 5' terminus served as PPAT substrates, but RNAs having <4 unpaired nucleotides did not undergo capping. No capping was observed when the +1A was changed to G or when 5' triphosphate was removed by RNA pyrophosphohydrolase (RppH), suggesting the enzyme recognizes pppA-RNA as an ATP analog. PPAT binding affinities were equivalent for transcripts with +1A, +1 G, or 5'OH (+1A), indicating that productive enzymatic recognition is driven more by local positioning effects than by overall binding affinity. Capping rates were independent of the number of unpaired nucleotides in the range of 4-10 nucleotides. Capping was strongly inhibited by ATP, reducing CoA-RNA production ~70% when equimolar ATP and substrate RNA were present. Dual bacterial expression of candidate RNAs with different 5' structures followed by CoA-RNA CaptureSeq revealed 12-fold enrichment of the better PPAT substrate, consistent with in vivo CoA-capping of RNA transcripts by PPAT. These results suggest post-transcriptional RNA capping as a possible mechanism for the biogenesis of CoA-RNAs in bacteria.

Advances in screening, synthesis, modification, and biomedical applications of peptides and peptide aptamers

Peptides and peptide aptamers have emerged as promising molecules for a wide range of biomedical applications due to their unique properties and versatile functionalities. The screening strategies for identifying peptides and peptide aptamers with desired properties are discussed, including high-throughput screening, display screening technology, and in silico design approaches. The synthesis methods for the efficient production of peptides and peptide aptamers, such as solid-phase peptide synthesis and biosynthesis technology, are described, along with their advantages and limitations. Moreover, various modification techniques are explored to enhance the stability, specificity, and pharmacokinetic properties of peptides and peptide aptamers. This includes chemical modifications, enzymatic modifications, biomodifications, genetic engineering modifications, and physical modifications. Furthermore, the review highlights the diverse biomedical applications of peptides and peptide aptamers, including targeted drug delivery, diagnostics, and therapeutic. This review provides valuable insights into the advancements in screening, synthesis, modification, and biomedical applications of peptides and peptide aptamers. A comprehensive understanding of these aspects will aid researchers in the development of novel peptide-based therapeutics and diagnostic tools for various biomedical challenges.

Acceleration of Protein Degradation by 20S Proteasome-Binding Peptides Generated by In Vitro Artificial Evolution

Although the 20S core particle (CP) of the proteasome is an important component of the 26S holoenzyme, the stand-alone 20S CP acts directly on intrinsically disordered and oxidized/damaged proteins to degrade them in a ubiquitin-independent manner. It has been postulated that some structural features of substrate proteins are recognized by the 20S CP to promote substrate uptake, but the mechanism of substrate recognition has not been fully elucidated. In this study, we screened peptides that bind to the 20S CP from a random eight-residue pool of amino acid sequences using complementary DNA display an in vitro molecular evolution technique. The identified 20S CP-binding amino acid sequence was chemically synthesized and its effects on the 20S CP were investigated. The 20S CP-binding peptide stimulated the proteolytic activity of the inactive form of 20S CP. The peptide bound directly to one of the α-subunits, opening a gate for substrate entry on the α-ring. Furthermore, the attachment of this peptide sequence to α-synuclein enhanced its degradation by the 20S CP in vitro. In addition to these results, docking simulations indicated that this peptide binds to the top surface of the α-ring. These peptides could function as a key to control the opening of the α-ring gate.

Differentiation SELEX approach identifies RNA aptamers with different specificities for HIV-1 capsid assembly forms

The HIV-1 capsid protein (CA) assumes distinct assembly forms during replication, each presenting unique, solvent-accessible surfaces that facilitate multifaceted functions and host factor interactions. However, contributions of individual CA assemblies remain unclear, as the evaluation of CA in cells presents several technical challenges. To address this need, we sought to identify CA assembly form-specific aptamers. Aptamer subsets with different specificities emerged from within a highly converged, pre-enriched aptamer library previously selected to bind the CA hexamer lattice. Subsets were either highly specific for CA lattice or bound both CA lattice and CA hexamer. We further evaluated four representatives to reveal aptamer structural features required for binding, highlighting interesting features and challenges in aptamer structure determination. Importantly, our aptamers bind biologically relevant forms of CA and we demonstrate aptamer-mediated affinity purification of CA from cell lysates without virus or host modification. Thus, we have identified CA assembly form-specific aptamers that represent exciting new tools for the study of CA.

Aptamer-Based Fentanyl Detection in Biological Fluids

Fentanyl is a widely abused analgesic and anesthetic drug with a narrow therapeutic window that creates easy opportunities for overdose and death. Rapid, accurate, and sensitive fentanyl detection in biosamples is crucial for therapeutic drug monitoring and overdose diagnosis. Unfortunately, current methods are limited to either sophisticated laboratory-based tests or antibody-based immunoassays, which are prone to false results and are mainly used with urine samples. Here, we have utilized library-immobilized SELEX to isolate new aptamers─nucleic acid-based bioreceptors that are well-suited for biosensing─that can specifically bind fentanyl under physiological conditions. We isolated multiple aptamers with nanomolar affinity and excellent specificity against dozens of interferents and incorporated one of these into an electrochemical aptamer-based sensor that can rapidly detect fentanyl at clinically relevant concentrations in 50% diluted serum, urine, and saliva. Given the excellent performance of these sensors, we believe that they could serve as the basis for point-of-care devices for monitoring fentanyl during medical procedures and determining fentanyl overdose.

Identification of the ATPase alpha subunit of Trypanosoma cruzi as a potential biomarker for the diagnosis of Chagas disease

BACKGROUND

Chagas disease (CD) is considered by the World Health Organisation (WHO) a neglected disease endemic to the Americas, but it has spread throughout the world due to migrations. The disease is almost 100% curable if detected in time. Still, the lack of rapid diagnostic tests with sufficient sensitivity and specificity leads to a chronic phase with a mortality of about 50,000 people worldwide per year.

METHODS

Using the total proteins extracted from serum samples of patients confirmed with chronic phase CD; we performed the Bio-SELEX strategy. The best aptamers were selected using next-generation sequencing (NGS) based on their most abundant sequences (reads and rpm). Then, selected aptamers were used to isolate potential biomarkers directly from serum samples of patients with chronic phase CD using pull-down and mass spectrometry experiments.

RESULTS

CH1 aptamer was the aptamer selected after the NGS results analysis. The pull-down and mass spectrometry experiments identified the presence of the ATPase alpha subunit of T. cruzi circulating in serum samples of patients with chronic phase CD.

CONCLUSIONS

We report the ATPase alpha subunit of T. cruzi as a potential biomarker for chronic phase CD and CH1 aptamer as a potential tool for diagnosing CD.

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.

Bio-SELEX: A Strategy for Biomarkers Isolation Directly from Biological Samples

Bio-SELEX is a revolutionary method for the discovery of novel biomarkers within biological samples, offering profound insights into diagnosing both infectious and non-infectious diseases. This innovative strategy involves three crucial steps: Traditional SELEX, Pull Down, and mass spectrometry. Firstly, Traditional SELEX involves the systematic selection of specific nucleic acid sequences (aptamers) that bind to the target molecules of interest. These aptamers are generated through iterative rounds of selection, amplification, and enrichment, ultimately yielding highly selective ligands. Secondly, the Pull-Down phase employs these aptamers to capture and isolate the target biomarkers from complex biological samples. This step ensures the specificity of the selected aptamers in binding to their intended targets. Lastly, mass spectrometry is utilized to identify and quantify the captured biomarkers, providing precise information about their presence and concentration in the sample. These quantitative data are invaluable in disease diagnosis and monitoring. Bio-SELEX's significance lies in its ability to discover biomarkers for a wide range of diseases, spanning infectious and non-infectious conditions. This approach holds great promise for early disease detection, personalized medicine, and the development of targeted therapies. By harnessing the power of aptamers and mass spectrometry, Bio-SELEX advances our understanding of disease biology and opens new avenues for improved healthcare.

Modified nucleic acid aptamers: development, characterization, and biological applications

Aptamers are single-stranded oligonucleotides that bind to their targets via specific structural interactions. To improve the properties and performance of aptamers, modified nucleotides are incorporated during or after a selection process such as systematic evolution of ligands by exponential enrichment (SELEX). We summarize the latest modified nucleotides and strategies used in modified (mod)-SELEX and post-SELEX to develop modified aptamers, highlight the methods used to characterize aptamer-target interactions, and present recent progress in modified aptamers that recognize different targets. We discuss the challenges and perspectives in further advancing the methodologies and toolsets to accelerate the discovery of modified aptamers, improve the throughput of aptamer-target characterization, and expand the functional diversity and complexity of modified aptamers.

New High-Affinity Thrombin Aptamers for Advancing Coagulation Therapy: Balancing Thrombin Inhibition for Clot Prevention and Effective Bleeding Management with Antidote

Thrombin is a key enzyme involved in blood clotting, and its dysregulation can lead to thrombotic diseases such as stroke, myocardial infarction, and deep vein thrombosis. Thrombin aptamers have the potential to be used as therapeutic agents to prevent or treat thrombotic diseases. Thrombin DNA aptamers developed in our laboratory exhibit high affinity and specificity to thrombin. In vitro assays have demonstrated their efficacy by significantly decreasing Factor II activity and increasing PT and APTT times in both plasma and whole blood. Aptamers AYA1809002 and AYA1809004, the two most potent aptamers, exhibit high affinity for their target, with affinity constants (Kd) of 10 nM and 13 nM, respectively. Furthermore, the in vitro activity of these aptamers displays dose-dependent behavior, highlighting their efficacy in a concentration-dependent manner. In vitro stability assessments reveal that the aptamers remain stable in plasma and whole blood for up to 24 h. This finding is crucial for their potential application in clinical settings. Importantly, the thrombin inhibitory activity of the aptamers can be reversed by employing reverse complement sequences, providing a mechanism to counteract their anticoagulant effects when necessary to avoid excessive bleeding. These thrombin aptamers have been determined to be safe, with no observed mutagenic or immunogenic effects. Overall, these findings highlight the promising characteristics of these newly developed thrombin DNA aptamers, emphasizing their potential for therapeutic applications in the field of anticoagulation therapy. Moreover, the inclusion of an antidote in the coagulation therapy regimen can improve patient safety, ensure greater therapeutic efficacy, and minimize risk during emergency situations.

Utilizing directed evolution to interrogate and optimize CRISPR/Cas guide RNA scaffolds

CRISPR-based editing has revolutionized genome engineering despite the observation that many DNA sequences remain challenging to target. Unproductive interactions formed between the single guide RNA's (sgRNA) Cas9-binding scaffold domain and DNA-binding antisense domain are often responsible for such limited editing resolution. To bypass this limitation, we develop a functional SELEX (systematic evolution of ligands by exponential enrichment) approach, termed BLADE (binding and ligand activated directed evolution), to identify numerous, diverse sgRNA variants that bind Streptococcus pyogenes Cas9 and support DNA cleavage. These variants demonstrate surprising malleability in sgRNA sequence. We also observe that particular variants partner more effectively with specific DNA-binding antisense domains, yielding combinations with enhanced editing efficiencies at various target sites. Using molecular evolution, CRISPR-based systems could be created to efficiently edit even challenging DNA sequences making the genome more tractable to engineering. This selection approach will be valuable for generating sgRNAs with a range of useful activities.

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.

Extending the dynamic range of biomarker quantification through molecular equalization

Precision medicine requires highly scalable methods of multiplexed biomarker quantification that can accurately describe patient physiology. Unfortunately, contemporary molecular detection methods are generally limited to a dynamic range of sensitivity spanning just 3-4 orders of magnitude, whereas the actual physiological dynamic range of the human plasma proteome spans more than 10 orders of magnitude. Current methods rely on sample splitting and differential dilution to compensate for this mismatch, but such measures greatly limit the reproducibility and scalability that can be achieved-in particular, the effects of non-linear dilution can greatly confound the analysis of multiplexed assays. We describe here a two-pronged strategy for equalizing the signal generated by each analyte in a multiplexed panel, thereby enabling simultaneous quantification of targets spanning a wide range of concentrations. We apply our 'EVROS' strategy to a proximity ligation assay and demonstrate simultaneous quantification of four analytes present at concentrations spanning from low femtomolar to mid-nanomolar levels. In this initial demonstration, we achieve a dynamic range spanning seven orders of magnitude in a single 5 µl sample of undiluted human serum, highlighting the opportunity to achieve sensitive, accurate detection of diverse analytes in a highly multiplexed fashion.

DAPTEV: Deep aptamer evolutionary modelling for COVID-19 drug design

Typical drug discovery and development processes are costly, time consuming and often biased by expert opinion. Aptamers are short, single-stranded oligonucleotides (RNA/DNA) that bind to target proteins and other types of biomolecules. Compared with small-molecule drugs, aptamers can bind to their targets with high affinity (binding strength) and specificity (uniquely interacting with the target only). The conventional development process for aptamers utilizes a manual process known as Systematic Evolution of Ligands by Exponential Enrichment (SELEX), which is costly, slow, dependent on library choice and often produces aptamers that are not optimized. To address these challenges, in this research, we create an intelligent approach, named DAPTEV, for generating and evolving aptamer sequences to support aptamer-based drug discovery and development. Using the COVID-19 spike protein as a target, our computational results suggest that DAPTEV is able to produce structurally complex aptamers with strong binding affinities.

Aptamers 101: aptamer discovery and in vitro applications in biosensors and separations

Aptamers are single-stranded nucleic acids that bind and recognize targets much like antibodies. Recently, aptamers have garnered increased interest due to their unique properties, including inexpensive production, simple chemical modification, and long-term stability. At the same time, aptamers possess similar binding affinity and specificity as their protein counterpart. In this review, we discuss the aptamer discovery process as well as aptamer applications to biosensors and separations. In the discovery section, we describe the major steps of the library selection process for aptamers, called systematic evolution of ligands by exponential enrichment (SELEX). We highlight common approaches and emerging strategies in SELEX, from starting library selection to aptamer-target binding characterization. In the applications section, we first evaluate recently developed aptamer biosensors for SARS-CoV-2 virus detection, including electrochemical aptamer-based sensors and lateral flow assays. Then we discuss aptamer-based separations for partitioning different molecules or cell types, especially for purifying T cell subsets for therapeutic applications. Overall, aptamers are promising biomolecular tools and the aptamer field is primed for expansion in biosensing and cell separation.

Discovery of DNA aptamers targeting SARS-CoV-2 nucleocapsid protein and protein-binding epitopes for label-free COVID-19 diagnostics

The spread of COVID-19 has affected billions of people across the globe, and the diagnosis of viral infection still needs improvement. Because of high immunogenicity and abundant expression during viral infection, SARS-CoV-2 nucleocapsid (N) protein could be an important diagnostic marker. This study aimed to develop a label-free optical aptasensor fabricated with a novel single-stranded DNA aptamer to detect the N protein. The N-binding aptamers selected using asymmetric-emulsion PCR-SELEX and their binding affinity and cross-reactivity were characterized by biolayer interferometry. The tNSP3 aptamer (44 nt) was identified to bind the N protein of wild type and Delta and Omicron variants with high affinity (K_D in the range of 0.6-3.5 nM). Utilizing tNSP3 to detect the N protein spiked in human saliva evinced the potential of this aptamer with a limit of detection of 4.5 nM. Mass spectrometry analysis was performed along with molecular dynamics simulation to obtain an insight into how tNSP3 binds to the N protein. The identified epitope peptides are localized within the RNA-binding domain and C terminus of the N protein. Hence, we confirmed the performance of this aptamer as an analytical tool for COVID-19 diagnosis.

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.

Aptamer-Assisted Proximity Ligation Assay for Sensitive Detection of Infectious Bronchitis Coronavirus

Infectious bronchitis virus (IBV) is a coronavirus responsible for major health problems in the poultry industry. New virus strains continue to appear, causing large economic losses. To develop a rapid and accurate new quantitative assay for diagnosis of the virus without DNA extraction, we selected highly specific single-stranded DNA (ssDNA) aptamers with a high affinity to IBV, using the systematic evolution of ligands by exponential enrichment (SELEX) technology for aptamer screening, followed by high-throughput sequencing technology. Two of these aptamers, AptIBV5 and AptIBV2, were used to establish homogenous and solid-phase proximity ligation assays (PLAs). The developed assays were evaluated for their sensitivity and specificity using collected field samples and then compared to the newly developed sandwich enzyme-linked aptamer assay (ELAA) and reverse transcription-quantitative PCR (qRT-PCR), as the gold-standard method. The solid-phase PLA showed a lower limit of detection and a broader dynamic range than the two other assays. The developed technique may serve as an alternative assay for the diagnosis of IBV, with the potential to be extended to the detection of other important animal or human viruses. IMPORTANCE Infectious bronchitis virus (IBV) causes high morbidity and mortality and large economic losses in the poultry industry. The virus has the ability to genetically mutate into new IBV strains, causing devastating disease and outbreaks. To better monitor the emergence of this virus, the development of a rapid and highly sensitive diagnostic method should be implemented. For this, we generated aptamers with high affinity and specificity to the IBV in an ssDNA library. Using two high-affinity aptamers, we developed a sandwich ELAA and a very sensitive aptamer-based proximity ligation assay (PLA). The new assay showed high sensitivity and specificity and was used to detect IBV in farm samples. The PLA was compared to the newly developed sandwich ELAA and qRT-PCR, as the gold-standard technique.

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.

Dual-specificity RNA aptamers enable manipulation of target-specific O-GlcNAcylation and unveil functions of O-GlcNAc on β-catenin

O-GlcNAc is a dynamic post-translational modification (PTM) that regulates protein functions. In studying the regulatory roles of O-GlcNAc, a major roadblock is the inability to change O-GlcNAcylation on a single protein at a time. Herein, we developed a dual RNA-aptamer-based approach that simultaneously targeted O-GlcNAc transferase (OGT) and β-catenin, the key transcription factor of the Wnt signaling pathway, to selectively increase O-GlcNAcylation of the latter without affecting other OGT substrates. Using the OGT/β-catenin dual-specificity aptamers, we found that O-GlcNAcylation of β-catenin stabilizes the protein by inhibiting its interaction with β-TrCP. O-GlcNAc also increases β-catenin's interaction with EZH2, recruits EZH2 to promoters, and dramatically alters the transcriptome. Further, by coupling riboswitches or an inducible expression system to aptamers, we enabled inducible regulation of protein-specific O-GlcNAcylation. Together, our findings demonstrate the efficacy and versatility of dual-specificity aptamers for regulating O-GlcNAcylation on individual proteins.

Systematic Study of in Vitro Selection Stringency Reveals How To Enrich High-Affinity Aptamers

Aptamers are oligonucleotide receptors with great potential for sensing and therapeutic applications. They are isolated from random libraries through an in vitro method termed systematic evolution of ligands by exponential enrichment (SELEX). Although SELEX-based methods have been widely employed over several decades, many aspects of the experimental process remain poorly understood in terms of how to adjust the selection conditions to obtain aptamers with the desired set of binding characteristics. As a result, SELEX is often performed with arbitrary parameters that tend to produce aptamers with insufficient affinity and/or specificity. Having a better understanding of these basic principles could increase the likelihood of obtaining high-quality aptamers. Here, we have systematically investigated how altering the selection stringency in terms of target concentration─which is essentially the root source of selection pressure for aptamer isolation─affects the outcome of SELEX. By performing four separate trials of SELEX for the same small-molecule target, we experimentally prove that the use of excessively high target concentrations promotes enrichment of low-affinity binders while also suppressing the enrichment of high-affinity aptamers. These findings should be broadly applicable across SELEX methods, given that they share the same core operating principle, and will be crucial for guiding selections to obtain high-quality aptamers in the future.

Exploiting natural riboswitches for aptamer engineering and validation

Over the past three decades, researchers have found that some engineered aptamers can be made to work well in test tubes but that these same aptamers might fail to function in cells. To help address this problem, we developed the 'Graftamer' approach, an experimental platform that exploits the architecture of a natural riboswitch to enhance in vitro aptamer selection and accelerate in vivo testing. Starting with combinatorial RNA pools that contain structural features of a guanine riboswitch aptamer interspersed with regions of random sequence, we performed multiplexed in vitro selection with a collection of small molecules. This effort yielded aptamers for quinine, guanine, and caffeine that appear to maintain structural features of the natural guanine riboswitch aptamer. Quinine and caffeine aptamers were each grafted onto a natural guanine riboswitch expression platform and reporter gene expression was monitored to determine that these aptamers function in cells. Additionally, we determined the secondary structure features and survival mechanism of a class of RNA sequences that evade the intended selection strategy, providing insight into improving this approach for future efforts. These results demonstrate that the Graftamer strategy described herein represents a convenient and straightforward approach to develop aptamers and validate their in vivo function.

Virtual screening of truncated single stranded DNA aptamers for Staphylococcal enterotoxin type A

Single stranded DNA (ssDNA)/RNA aptamers, are screened through the labor intensive, iterative Systematic Evolution of Ligand by Exponential Enrichment process (SELEX) method. Complete sequence of screened aptamers never interacts with target or participates in final structure. Hence, in silico tools can be used to redesign a short length aptamer from previously reported aptamers which can have high affinity and specificity to the target. This approach is fast, cost effective, and less laborious than in vitro SELEX towards finding an aptamer sequence with better affinity with the target. Here, Staphylococcal enterotoxin type A (SEA) was used as target. A total of nine aptamers reported for different Staphylococcal food poisoning (SFP) enterotoxins were used as a starting pool. The aptamers were variously truncations and thoroughly analyzed through in silico methods. Three truncated aptamers namely AptSEA1.4, AptSEA2.4 and AptSEA8.4 were found to show higher affinity with target SEA. The computational data was also validated with DOT BLOT assay complemented with image analysis. These results also confirmed that the % specific binding and the dissociation constant (Kd) of truncated aptamers AptSEA1.4, AptSEA2.4 and AptSEA8.4 was better than their original counterparts. The truncated aptamers showed great promise to be used as a capture reagent in developing a sensitive assay for detection of SEA.Communicated by Ramaswamy H. Sarma.

Discovery of Aptamers Against Cell Surface Markers Using Ligand-Guided Selection

Oligonucleotide ligands (DNA, RNA, or XNA), also known as aptamers, are selected against various target molecules using an iterative, evolutionary process called systematic evolution of ligands by exponential enrichment (SELEX). To select aptamers against complex cell surface proteins in their native state, a variant of SELEX termed ligand-guided selection (LIGS) was recently introduced. The significance of LIGS is rooted in its strategy of exploiting the selection step in SELEX to identify highly specific aptamers against known cell surface markers. Thus, in LIGS, a higher-affinity secondary ligand, such as a monoclonal antibody (mAb) to a whole-cell bound to an evolved SELEX library, is introduced to outcompete sequences against the mAb targeting cell surface protein or induce a conformational switch to destabilize the aptamer-surface cell surface protein resulting in elution of the sequences. Here, we describe the detailed method of LIGS utilized in identifying aptamers against T-cell receptor cluster of differentiation three complex (TCR-CD3) expressed in human T-cells and T-cell leukemia.

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).

Inhibition of α-Synuclein Seeding-Dependent Aggregation by ssDNA Aptamers Specific to C-Terminally Truncated α-Synuclein Fibrils

Neuropathologically, Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are characterized by the accumulation of insoluble aggregates of α-synuclein (α-syn) in the Lewy bodies (LBs). In addition to full-length α-syn fibrils, C-terminally truncated α-syn is also abundant in the LBs that acts as seeds and facilitates the aggregation of the full-length α-syn in vitro and in vivo and induces toxicity. Hence, identifying molecules that can inhibit the seeding activity of these truncated forms is of great importance. Here, we report the first in vitro selection of aptamers targeting the fibrillar forms of different C-terminally truncated α-syn using systematic evolution by an exponential enrichment method followed by quantitative high-throughput DNA sequencing. We identify a panel of aptamers that bound with high specificity to different truncated forms of α-syn fibrils with no cross-reactivity toward other amyloid fibrils. Interestingly, two of the aptamers (named Apt11 and Apt15) show higher affinity to most C-terminally truncated forms of α-syn fibrils with an evident inhibition of α-syn-seeded aggregation in vitro by Apt11. This inhibition is further confirmed by circular dichroism, Congo red binding assay, and electronic microscopy. Moreover, Apt11 is also found to reduce the insoluble phosphorylated form of α-syn at Ser-129 (pS129-α-syn) in the cell model and also can inhibit α-syn aggregation using RT-QuIC reactions seeded with brain homogenates extracted from patients affected by PD. The aptamers discovered in this study represent potential useful tools for research and diagnostics or therapy toward PD and DLB.

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?

Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.

SELEX: Critical factors and optimization strategies for successful aptamer selection

Within the last decade, the application range of aptamers in biochemistry and medicine has expanded rapidly. More than just a replacement for antibodies, these intrinsically structured RNA- or DNA-oligonucleotides show great potential for utilization in diagnostics, specific drug delivery, and treatment of certain medical conditions. However, what is analyzed less frequently is the process of aptamer identification known as systematic evolution of ligands by exponential enrichment (SELEX) and the functional mechanisms that lie at its core. SELEX involves numerous singular processes, each of which contributes to the success or failure of aptamer generation. In this review, critical steps during aptamer selection are discussed in-depth, and specific problems are presented along with potential solutions. The discussed aspects include the size and molecule type of the selected target, the nature and stringency of the selection process, the amplification step with its possible PCR bias, the efficient regeneration of RNA or single-stranded DNA, and the different sequencing procedures and screening assays currently available. Finally, useful quality control steps and their role within SELEX are presented. By understanding the mechanisms through which aptamer selection is influenced, the design of more efficient SELEX procedures leading to a higher success rate in aptamer identification is enabled.

Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection

Selection protocols such as SELEX, where molecules are selected over multiple rounds for their ability to bind to a target of interest, are popular methods for obtaining binders for diagnostic and therapeutic purposes. We show that Restricted Boltzmann Machines (RBMs), an unsupervised two-layer neural network architecture, can successfully be trained on sequence ensembles from single rounds of SELEX experiments for thrombin aptamers. RBMs assign scores to sequences that can be directly related to their fitnesses estimated through experimental enrichment ratios. Hence, RBMs trained from sequence data at a given round can be used to predict the effects of selection at later rounds. Moreover, the parameters of the trained RBMs are interpretable and identify functional features contributing most to sequence fitness. To exploit the generative capabilities of RBMs, we introduce two different training protocols: one taking into account sequence counts, capable of identifying the few best binders, and another based on unique sequences only, generating more diverse binders. We then use RBMs model to generate novel aptamers with putative disruptive mutations or good binding properties, and validate the generated sequences with gel shift assay experiments. Finally, we compare the RBM’s performance with different supervised learning approaches that include random forests and several deep neural network architectures.

We show that two-layer neural networks, Restricted Boltzmann Machines (RBM), can be successfully trained on sequence ensemble datasets from selection-amplification experiments. We train the RBM using datasets from aptamer selection experiments on thrombin protein, and show that the model can successfully generalize to the test set to predict binders and non-binders. The log-likelihood assigned to a sequence by the RBM is correlated with the sequence fitness as quantified by the amplification between different rounds of selection. We further show that that the model is interpretable and by inspecting the weights of the model, we can identify structural motifs that are characteristic of the good binders. We explore the usage of the RBMs to identify which of the possible protein exosites the aptamers bind to. We show that the RBM can also be used for unsupervised clustering. Finally, we use RBMs to generate novel aptamers, and we experimentally verify predicted binding and non-binding sequences generated from the RBM.

A scalable framework for the discovery of functional helicase substrates and helicase-driven regulatory switches

Helicases are ubiquitous motor enzymes that remodel nucleic acids (NA) and NA-protein complexes in key cellular processes. To explore the functional repertoire and specificity landscape of helicases, we devised a screening scheme-Helicase-SELEX (Systematic Evolution of Ligands by EXponential enrichment)-that enzymatically probes substrate and cofactor requirements at global scale. Using the transcription termination Rho helicase of Escherichia coli as a prototype for Helicase-SELEX, we generated a genome-wide map of Rho utilization (Rut) sites. The map reveals many features, including promoter- and intrinsic terminator-associated Rut sites, bidirectional Rut tandems, and cofactor-dependent Rut sites with inverted G > C skewed compositions. We also implemented an H-SELEX variant where we used a model ligand, serotonin, to evolve synthetic Rut sites operating in vitro and in vivo in a ligand-dependent manner. Altogether, our data illustrate the power and flexibility of Helicase-SELEX to seek constitutive or conditional helicase substrates in natural or synthetic NA libraries for fundamental or synthetic biology discovery.

Selection and characterization of bispecific aptamers against malachite green and leucomalachite green

In order to develop multi-residues rapid detection, the bispecific aptamers against malachite green (MG) and leucomalachite green (LMG) were isolated by the capture systematic evolution of ligands by exponential enrichment (Capture-SELEX). After thirteen rounds of selection, the enriched ssDNA pools were sent for high-throughput sequencing. Nine aptamer candidates (A1-A9) were picked out to test their specificity by gold nanoparticles (AuNPs) colorimetric assay. Three aptamers (A2, A3, A5) with good selectivity were truncated to verify their affinity by fluorescence assay. Finally, three truncated aptamers (A2-a, A3-a, A5-a) with bispecificity and high affinity were identified. For LMG, the dissociation constant (Kd) of them were 8.4 ± 0.8 nM, 8.2 ± 1.2 nM, and 13.7 ± 1.4 nM, respectively. For MG, Kd of them were 3.4 ± 0.3 μM, 2.3 ± 0.2 μM, 3.0 ± 0.2μM. Among them, A3-a is the best. Our work will provide novel probes for the development of multi-residues rapid detection as well as opportunities for multiple target aptamer discovery.

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.

Discovery of a Transferrin Receptor 1-Binding Aptamer and Its Application in Cancer Cell Depletion for Adoptive T-Cell Therapy Manufacturing

The clinical manufacturing of chimeric antigen receptor (CAR) T cells includes cell selection, activation, gene transduction, and expansion. While the method of T-cell selection varies across companies, current methods do not actively eliminate the cancer cells in the patient's apheresis product from the healthy immune cells. Alarmingly, it has been found that transduction of a single leukemic B cell with the CAR gene can confer resistance to CAR T-cell therapy and lead to treatment failure. In this study, we report the identification of a novel high-affinity DNA aptamer, termed tJBA8.1, that binds transferrin receptor 1 (TfR1), a receptor broadly upregulated by cancer cells. Using competition assays, high resolution cryo-EM, and de novo model building of the aptamer into the resulting electron density, we reveal that tJBA8.1 shares a binding site on TfR1 with holo-transferrin, the natural ligand of TfR1. We use tJBA8.1 to effectively deplete B lymphoma cells spiked into peripheral blood mononuclear cells with minimal impact on the healthy immune cell composition. Lastly, we present opportunities for affinity improvement of tJBA8.1. As TfR1 expression is broadly upregulated in many cancers, including difficult-to-treat T-cell leukemias and lymphomas, our work provides a facile, universal, and inexpensive approach for comprehensively removing cancerous cells from patient apheresis products for safe manufacturing of adoptive T-cell therapies.

An In Vitro Selection Platform to Identify Multiple Aptamers against Multiple Cell-Surface Markers Using Ligand-Guided Selection

Aptamer ligand discovery against multiple molecules expressed on whole cells is an essential component in molecular tool development. However, owing to their intrinsic structural characteristics, cell-surface receptors have proven to be challenging targets in ligand discovery. Several variants to systematic evolution of ligands by exponential enrichment (SELEX) have been introduced to address the ″target problem″ for aptamer screening. To this end, we introduced a variant of SELEX, termed ligand-guided selection (LIGS), to identify highly specific aptamers against complex cell-surface markers in their native state. So far, the application of LIGS has been aimed at identifying aptamers against the most dominant receptors on the cell surface. Here, we report that LIGS can be expanded to identify two receptors on the same cell surface, paving the way to generate a multiplexed ligand discovery platform based on SELEX-targeting membrane receptors in their native functional state. Using CD19 and CD20 expressed on Toledo cells as a model system, multiple aptamer families were evolved against Toledo cells. We then utilized two monoclonal antibodies (mAbs) against CD20 and CD19 to selectively partition specific aptamers against CD19 and CD20. Following biochemical characterization, we introduce two specific aptamers against CD19 and two specific aptamers against CD20 with high affinity. Multi-target LIGS, as reported here, demonstrates a successful combinatorial approach for nucleic acid library screening to generate multiple artificial nucleic acid ligands against multiple receptors expressed on a single cell.

Uncovering temporospatial sensitive TBI targeting strategies via in vivo phage display

The heterogeneous pathophysiology of traumatic brain injury (TBI) is a barrier to advancing diagnostics and therapeutics, including targeted drug delivery. We used a unique discovery pipeline to identify novel targeting motifs that recognize specific temporal phases of TBI pathology. This pipeline combined in vivo biopanning with domain antibody (dAb) phage display, next-generation sequencing analysis, and peptide synthesis. We identified targeting motifs based on the complementarity-determining region 3 structure of dAbs for acute (1 day post-injury) and subacute (7 days post-injury) post-injury time points in a preclinical TBI model (controlled cortical impact). Bioreactivity and temporal sensitivity of the targeting motifs were validated via immunohistochemistry. Immunoprecipitation-mass spectrometry indicated that the acute TBI targeting motif recognized targets associated with metabolic and mitochondrial dysfunction, whereas the subacute TBI motif was largely associated with neurodegenerative processes. This pipeline successfully discovered temporally specific TBI targeting motif/epitope pairs that will serve as the foundation for the next-generation targeted TBI therapeutics and diagnostics.

REVERSE: a user-friendly web server for analyzing next-generation sequencing data from in vitro selection/evolution experiments

Next-generation sequencing (NGS) enables the identification of functional nucleic acid sequences from in vitro selection/evolution experiments and illuminates the evolutionary process at single-nucleotide resolution. However, analyzing the vast output from NGS can be daunting, especially with limited programming skills. We developed REVERSE (Rapid EValuation of Experimental RNA Selection/Evolution) (https://www.reverseserver.org/), a web server that implements an integrated computational pipeline through a graphical user interface, which performs both pre-processing and detailed sequence level analyses within minutes. Raw FASTQ files are quality-filtered, dereplicated, and trimmed before being analyzed by either of two pipelines. The first pipeline counts, sorts, and tracks enrichment of unique sequences and user-defined sequence motifs. It also identifies mutational intermediates present in the sequence data that connect two input sequences. The second pipeline sorts similar sequences into clusters and tracks enrichment of peak sequences. It also performs nucleotide conservation analysis on the cluster of choice and generates a consensus sequence. Both pipelines generate downloadable spreadsheets and high-resolution figures. Collectively, REVERSE is a one-stop solution for the rapid analysis of NGS data obtained from in vitro selection/evolution experiments that obviates the need for computational expertise.

Nucleic Acid Aptamers Emerging as Modulators of G-Protein-Coupled Receptors: Challenge to Difficult Cell Surface Proteins

G-protein-coupled receptors (GPCRs), among various cell surface proteins, are essential targets in the fields of basic science and drug discovery. The discovery and development of modulators for the receptors have provided deep insights into the mechanism of action of receptors and have led to a new therapeutic option for human diseases. Although various modulators against GPCRs have been developed to date, the identification of new modulators for GPCRs remains a challenge due to several technical problems and limitations. To overcome this situation, a variety of strategies have been developed by several modalities, including nucleic acid aptamers, which are emerging as unique molecules isolated by a repetitive selection process against various types of targets from an enormous combinatorial library. This review summarized the achievements in the development of aptamers targeting GPCRs, and discussed their isolation methods and the diverse functional features of aptamers against GPCRs.

Generation and Selection of Specific Aptamers Targeting Brucella Species through an Enhanced Cell-SELEX Methodology

Brucellae are Gram-negative, aerobic, non-motile coccobacilli causing brucellosis in man and animals. The disease is one of the most significant yet neglected global zoonoses. Especially in developing countries, brucellosis is causing public health problems and economic losses to private animal owners and national revenues. Composed of oligonucleotides, aptamers are chemical analogues of antibodies that are promising components for developing aptamer-based rapid, sensitive, and specific tests to identify the Brucella group of bacteria. For this purpose, aptamers were generated and selected by an enhanced protocol of cell systematic evolution of ligands by exponential enrichment (cell-SELEX). This enhanced cell-SELEX procedure involved the combination of both conventional and toggle cell-SELEX to boost the specificity and binding affinity to whole Brucella cells. This procedure, combined with high-throughput sequencing of the resulting aptamer pools, comprehensive bioinformatics analysis, and wet lab validation assays, led to the selection of a highly sensitive and specific aptamer for those Brucella species known to circulate in Egypt. The isolated candidate aptamer showed dissociation constant (K_D) values of 43.5 ± 11, 61.5 ± 8, and 56 ± 10.8 nM for B. melitensis, B. abortus, and B. suis, respectively. This is the first development of a Brucella-specific aptamer using an enhanced combination of conventional and toggle cell-SELEX to the authors’ best knowledge.

Aptamers as promising nanotheranostic tools in the COVID-19 pandemic era

The emergence of SARS‐COV‐2, the causative agent of new coronavirus disease (COVID‐19) has become a pandemic threat. Early and precise detection of the virus is vital for effective diagnosis and treatment. Various testing kits and assays, including nucleic acid detection methods, antigen tests, serological tests, and enzyme‐linked immunosorbent assay (ELISA), have been implemented or are being explored to detect the virus and/or characterize cellular and antibody responses to the infection. However, these approaches have inherent drawbacks such as nonspecificity, high cost, are characterized by long turnaround times for test results, and can be labor‐intensive. Also, the circulating SARS‐COV‐2 variant of concerns, reduced antibody sensitivity and/or neutralization, and possible antibody‐dependent enhancement (ADE) have warranted the search for alternative potent therapeutics. Aptamers, which are single‐stranded oligonucleotides, generated artificially by SELEX (Evolution of Ligands by Exponential Enrichment) may offer the capacity to generate high‐affinity neutralizers and/or bioprobes for monitoring relevant SARS‐COV‐2 and COVID‐19 biomarkers. This article reviews and discusses the prospects of implementing aptamers for rapid point‐of‐care detection and treatment of SARS‐COV‐2. We highlight other SARS‐COV‐2 targets (N protein, spike protein stem‐helix), SELEX augmented with competition assays and in silico technologies for rapid discovery and isolation of theranostic aptamers against COVID‐19 and future pandemics. It further provides an overview on site‐specific bioconjugation approaches, customizable molecular scaffolding strategies, and nanotechnology platforms to engineer these aptamers into ultrapotent blockers, multivalent therapeutics, and vaccines to boost both humoral and cellular immunity against the virus.

This article is categorized under:

Therapeutic Approaches and Drug Discovery > Emerging Technologies

Diagnostic Tools > Biosensing

Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease

Therapeutic Approaches and Drug Discovery > Nanomedicine for Respiratory Disease

MAVE-NN: learning genotype-phenotype maps from multiplex assays of variant effect

Multiplex assays of variant effect (MAVEs) are a family of methods that includes deep mutational scanning experiments on proteins and massively parallel reporter assays on gene regulatory sequences. Despite their increasing popularity, a general strategy for inferring quantitative models of genotype-phenotype maps from MAVE data is lacking. Here we introduce MAVE-NN, a neural-network-based Python package that implements a broadly applicable information-theoretic framework for learning genotype-phenotype maps—including biophysically interpretable models—from MAVE datasets. We demonstrate MAVE-NN in multiple biological contexts, and highlight the ability of our approach to deconvolve mutational effects from otherwise confounding experimental nonlinearities and noise.