DNA-binding specificities of human transcription factors.

Although the proteins that read the gene regulatory code, transcription factors (TFs), have been largely identified, it is not well known which sequences TFs can recognize. We have analyzed the sequence-specific binding of human TFs using high-throughput SELEX and ChIP sequencing. A total of 830 binding profiles were obtained, describing 239 distinctly different binding specificities. The models represent the majority of human TFs, approximately doubling the coverage compared to existing systematic studies. Our results reveal additional specificity determinants for a large number of factors for which a partial specificity was known, including a commonly observed A- or T-rich stretch that flanks the core motifs. Global analysis of the data revealed that homodimer orientation and spacing preferences, and base-stacking interactions, have a larger role in TF-DNA binding than previously appreciated. We further describe a binding model incorporating these features that is required to understand binding of TFs to DNA.

Systematic analysis of binding of transcription factors to noncoding variants.

Many sequence variants have been linked to complex human traits and diseases1, but deciphering their biological functions remains challenging, as most of them reside in noncoding DNA. Here we have systematically assessed the binding of 270 human transcription factors to 95,886 noncoding variants in the human genome using an ultra-high-throughput multiplex protein-DNA binding assay, termed single-nucleotide polymorphism evaluation by systematic evolution of ligands by exponential enrichment (SNP-SELEX). The resulting 828 million measurements of transcription factor-DNA interactions enable estimation of the relative affinity of these transcription factors to each variant in vitro and evaluation of the current methods to predict the effects of noncoding variants on transcription factor binding. We show that the position weight matrices of most transcription factors lack sufficient predictive power, whereas the support vector machine combined with the gapped k-mer representation show much improved performance, when assessed on results from independent SNP-SELEX experiments involving a new set of 61,020 sequence variants. We report highly predictive models for 94 human transcription factors and demonstrate their utility in genome-wide association studies and understanding of the molecular pathways involved in diverse human traits and diseases.

AptaDB: a comprehensive database integrating aptamer-target interactions.

Aptamers have emerged as research hotspots of the next generation due to excellent performance benefits and application potentials in pharmacology, medicine, and analytical chemistry. Despite the numerous aptamer investigations, the lack of comprehensive data integration has hindered the development of computational methods for aptamers and the reuse of aptamers. A public access database named AptaDB, derived from experimentally validated data manually collected from the literature, was hence developed, integrating comprehensive aptamer-related data, which include six key components: (i) experimentally validated aptamer-target interaction information, (ii) aptamer property information, (iii) structure information of aptamer, (iv) target information, (v) experimental activity information, and (vi) algorithmically calculated similar aptamers. AptaDB currently contains 1350 experimentally validated aptamer-target interactions, 1230 binding affinity constants, 1293 aptamer sequences, and more. Compared to other aptamer databases, it contains twice the number of entries found in available databases. The collection and integration of the above information categories is unique among available aptamer databases and provides a user-friendly interface. AptaDB will also be continuously updated as aptamer research evolves. We expect that AptaDB will become a powerful source for aptamer rational design and a valuable tool for aptamer screening in the future. For access to AptaDB, please visit http://lmmd.ecust.edu.cn/aptadb/.

AptaDiff: de novo design and optimization of aptamers based on diffusion models.

Aptamers are single-stranded nucleic acid ligands, featuring high affinity and specificity to target molecules. Traditionally they are identified from large DNA/RNA libraries using $in vitro$ methods, like Systematic Evolution of Ligands by Exponential Enrichment (SELEX). However, these libraries capture only a small fraction of theoretical sequence space, and various aptamer candidates are constrained by actual sequencing capabilities from the experiment. Addressing this, we proposed AptaDiff, the first in silico aptamer design and optimization method based on the diffusion model. Our Aptadiff can generate aptamers beyond the constraints of high-throughput sequencing data, leveraging motif-dependent latent embeddings from variational autoencoder, and can optimize aptamers by affinity-guided aptamer generation according to Bayesian optimization. Comparative evaluations revealed AptaDiff's superiority over existing aptamer generation methods in terms of quality and fidelity across four high-throughput screening data targeting distinct proteins. Moreover, surface plasmon resonance experiments were conducted to validate the binding affinity of aptamers generated through Bayesian optimization for two target proteins. The results unveiled a significant boost of $87.9\%$ and $60.2\%$ in RU values, along with a 3.6-fold and 2.4-fold decrease in KD values for the respective target proteins. Notably, the optimized aptamers demonstrated superior binding affinity compared to top experimental candidates selected through SELEX, underscoring the promising outcomes of our AptaDiff in accelerating the discovery of superior aptamers.

Minimizing amplification bias during reverse transcription for in vitro selections.

Systematic evolution of ligands through exponential enrichment (SELEX) is widely used to identify functional nucleic acids, such as aptamers and ribozymes. Ideally, selective pressure drives the enrichment of sequences that display the function of interest (binding, catalysis, etc.). However, amplification biases from reverse transcription can overwhelm this enrichment and leave some functional sequences at a disadvantage, with cumulative effects across multiple rounds of selection. Libraries that are designed to include structural scaffolds can improve selection outcomes by sampling sequence space more strategically, but they are also susceptible to such amplification biases, particularly during reverse transcription. Therefore, we tested five reverse transcriptases (RTs)-ImProm-II, Marathon RT (MaRT), TGIRT-III, SuperScript IV (SSIV), and BST 3.0 DNA polymerase (BST)-to determine which enzymes introduced the least bias. We directly compared cDNA yield and processivity for these enzymes on RNA templates with varying degrees of structure under various reaction conditions. In these analyses, BST exhibited excellent processivity, generated large quantities of the full-length cDNA product, displayed little bias among templates with varying structure and sequence, and performed well on long, highly structured viral RNAs. Additionally, six RNA libraries containing either strong, moderate, or no incorporated structural elements were pooled and competed head-to-head in six rounds of an amplification-only selection without external selective pressure using either SSIV, ImProm-II, or BST during reverse transcription. High-throughput sequencing established that BST maintained the most neutral enrichment values, indicating low interlibrary bias over the course of six rounds, relative to SSIV and ImProm-II, and it introduced minimal mutational bias.

Aptamer-Protein Interactions: From Regulation to Biomolecular Detection.

Serving as the basis of cell life, interactions between nucleic acids and proteins play essential roles in fundamental cellular processes. Aptamers are unique single-stranded oligonucleotides generated by in vitro evolution methods, possessing the ability to interact with proteins specifically. Altering the structure of aptamers will largely modulate their interactions with proteins and further affect related cellular behaviors. Recently, with the in-depth research of aptamer-protein interactions, the analytical assays based on their interactions have been widely developed and become a powerful tool for biomolecular detection. There are some insightful reviews on aptamers applied in protein detection, while few systematic discussions are from the perspective of regulating aptamer-protein interactions. Herein, we comprehensively introduce the methods for regulating aptamer-protein interactions and elaborate on the detection techniques for analyzing aptamer-protein interactions. Additionally, this review provides a broad summary of analytical assays based on the regulation of aptamer-protein interactions for detecting biomolecules. Finally, we present our perspectives regarding the opportunities and challenges of analytical assays for biological analysis, aiming to provide guidance for disease mechanism research and drug discovery.

Natural RNA Polymerase Aptamers Regulate Transcription in E. coli.

In search for RNA signals that modulate transcription via direct interaction with RNA polymerase (RNAP), we deep sequenced an E. coli genomic library enriched for RNAP-binding RNAs. Many natural RNAP-binding aptamers, termed RAPs, were mapped to the genome. Over 60% of E. coli genes carry RAPs in their mRNA. Combining in vitro and in vivo approaches, we characterized a subset of inhibitory RAPs (iRAPs) that promote Rho-dependent transcription termination. A representative iRAP within the coding region of the essential gene, nadD, greatly reduces its transcriptional output in stationary phase and under oxidative stress, demonstrating that iRAPs control gene expression in response to changing environment. The mechanism of iRAPs involves active uncoupling of transcription and translation, making nascent RNA accessible to Rho. iRAPs encoded in the antisense strand also promote gene expression by reducing transcriptional interference. In essence, our work uncovers a broad class of cis-acting RNA signals that globally control bacterial transcription.

Characterization of an HNA aptamer suggests a non-canonical G-quadruplex motif.

Nucleic acids not only form the basis of heredity, but are increasingly a source of novel nano-structures, -devices and drugs. This has spurred the development of chemically modified alternatives (xeno nucleic acids (XNAs)) comprising chemical configurations not found in nature to extend their chemical and functional scope. XNAs can be evolved into ligands (XNA aptamers) that bind their targets with high affinity and specificity. However, detailed investigations into structural and functional aspects of XNA aptamers have been limited. Here we describe a detailed structure-function analysis of LYS-S8-19, a 1',5'-anhydrohexitol nucleic acid (HNA) aptamer to hen egg-white lysozyme (HEL). Mapping of the aptamer interaction interface with its cognate HEL target antigen revealed interaction epitopes, affinities, kinetics and hot-spots of binding energy similar to protein ligands such as anti-HEL-nanobodies. Truncation analysis and molecular dynamics (MD) simulations suggest that the HNA aptamer core motif folds into a novel and not previously observed HNA tertiary structure, comprising non-canonical hT-hA-hT/hT-hT-hT triplet and hG4-quadruplex structures, consistent with its recognition by two different G4-specific antibodies.

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.

Selection of allosteric dnazymes that can sense phenylalanine by expression-SELEX.

Aptamers are ligand-binding RNA or DNA molecules and have been widely examined as biosensors, diagnostic tools, and therapeutic agents. The application of aptamers as biosensors commonly requires an expression platform to produce a signal to report the aptamer-ligand binding event. Traditionally, aptamer selection and expression platform integration are two independent steps and the aptamer selection requires the immobilization of either the aptamer or the ligand. These drawbacks can be easily overcome through the selection of allosteric DNAzymes (aptazymes). Herein, we used the technique of Expression-SELEX developed in our laboratory to select for aptazymes that can be specifically activated by low concentrations of l-phenylalanine. We chose a previous DNA-cleaving DNAzyme known as II-R1 as the expression platform for its low cleavage rate and used stringent selection conditions to drive the selection of high-performance aptazyme candidates. Three aptazymes were chosen for detailed characterization and these DNAzymes were found to exhibit a dissociation constant for l-phenylalanine as low as 4.8 µM, a catalytic rate constant improvement as high as 20 000-fold in the presence of l-phenylalanine, and the ability to discriminate against closely related l-phenylalanine analogs including d-phenylalanine. This work has established the Expression-SELEX as an effective SELEX method to enrich high-quality ligand-responsive aptazymes.

A system for multiplexed selection of aptamers with exquisite specificity without counterselection.

Aptamers have proven to be valuable tools for the detection of small molecules due to their remarkable ability to specifically discriminate between structurally similar molecules. Most aptamer selection efforts have relied on counterselection to eliminate aptamers that exhibit unwanted cross-reactivity to interferents or structurally similar relatives to the target of interest. However, because the affinity and specificity characteristics of an aptamer library are fundamentally unknowable a priori, it is not possible to determine the optimal counterselection parameters. As a result, counterselection experiments require trial-and-error approaches that are inherently inefficient and may not result in aptamers with the best combination of affinity and specificity. In this work, we describe a high-throughput screening process for generating high-specificity aptamers to multiple targets in parallel while also eliminating the need for counterselection. We employ a platform based on a modified benchtop sequencer to conduct a massively parallel aptamer screening process that enables the selection of highly specific aptamers against multiple structurally similar molecules in a single experiment, without any counterselection. As a demonstration, we have selected aptamers with high affinity and exquisite specificity for three structurally similar kynurenine metabolites that differ by a single hydroxyl group in a single selection experiment. This process can easily be adapted to other small-molecule analytes and should greatly accelerate the development of aptamer reagents that achieve exquisite specificity for their target analytes.

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.

Elucidation of CKAP4-remodeled cell mechanics in driving metastasis of bladder cancer through aptamer-based target discovery.

Metastasis contributes to the dismal prognosis of bladder cancer (BLCA). The mechanical status of the cell membrane is expected to mirror the ability of cell migration to promote cancer metastasis. However, the mechanical characteristics and underlying molecular profile associated with BLCA metastasis remain obscure. To study the unique cellular architecture and traits associated with cell migration, using a process called cell-based systematic evolution of ligands by exponential enrichment (cell-SELEX) we generated an aptamer-based molecular probe, termed spl3c, which identified cytoskeleton-associated protein 4 (CKAP4). CKAP4 was associated with tumor metastasis in BLCA, but we also found it to be a mechanical regulator of BLCA cells through the maintenance of a central-to-peripheral gradient of stiffness on the cell membrane. Notably, such mechanical traits were transportable through exosome-mediated intercellular CKAP4 trafficking, leading to significant enhancement of migration in recipient cells and, consequently, aggravating metastatic potential in vivo. Taken together, our study shows the robustness of this aptamer-based molecular tool for biomarker discovery, revealing the dominance of a CKAP4-induced central-to-peripheral gradient of membrane stiffness that benefits cell migration and delineating the role of exosomes in mediating mechanical signaling in BLCA metastasis.

Selection of internalizing RNA aptamers into human breast cancer cells derived from primary sites.

Breast cancer is the most common cancer in women. Although chemotherapy is still broadly used in its treatment, adverse effects remain a challenge. In this scenario, aptamers emerge as a promising alternative for theranostic applications. Studies using breast cancer cell lines provide useful information in laboratory and preclinical investigations, most of which use cell lines established from metastatic sites. However, these cell lines correspond to cell populations of the late stage of tumor progression. On the other hand, studies using breast cancer cells established from primary sites make it possible to search for new theranostic approaches in the early stages of the disease. Therefore, this work aimed to select RNA aptamers internalized by MGSO-3 cells, a human breast cancer cell line, derived from a primary site previously established in our laboratory. Using the Cell-Internalization SELEX method, we have selected two candidate aptamers (ApBC1 and ApBC2). We evaluated their internalization efficiencies, specificities, cellular localization by Reverse Transcription-qPCR (RT-qPCR) and confocal microscopy assays. The results suggest that both aptamers were efficiently internalized by human breast cancer cells, MACL-1, MDA-MB-231, and especially by MGSO-3 cells. Furthermore, both aptamers could effectively distinguish human breast cancer cells derived from normal human mammary cell (MCF 10A) and prostate cancer cell (PC3) lines. Therefore, ApBC1 and ApBC2 could be promising candidate molecules for theranostic applications, even in the early stages of tumor progression.

Rapid Nuclease-Assisted Selection of High-Affinity Small-Molecule Aptamers.

Aptamers are nucleic acid bioreceptors that have been widely utilized for a variety of biosensing applications, including in vivo detection methods that would not be possible with antibody-based systems. However, it remains challenging to generate high-quality aptamers for small molecule targets, particularly for use under physiological conditions. We present a highly effective aptamer selection technology for small-molecule targets that utilizes the nuclease EcoRI to remove nonspecific or weakly binding sequences in solution phase, rapidly enriching high-affinity target binders within just a few rounds of selection. As proof-of-concept, we used our nuclease-assisted SELEX (NA-SELEX) method to isolate aptamers for a synthetic cannabinoid, AB-FUBINACA. Within five rounds, we identified two highly specific aptamers that exhibit nanomolar affinity at physiological temperature. We also demonstrate the robustness and reproducibility of NA-SELEX by performing the same selection experiment with fresh reagents and libraries, obtaining the same two aptamers as well as two other high-quality aptamer candidates. Finally, we compare NA-SELEX against a conventional library-immobilized SELEX screen for AB-FUBINACA using the same screening conditions, identifying aptamers with 25-100-fold weaker affinity after 11 rounds of selection. NA-SELEX therefore could be an effective selection method for the isolation of high-quality aptamers for small-molecule targets.

Efficient Strategy to Discover DNA Aptamers Against Low Abundance Cell Surface Proteins in Scarce Samples.

Molecular recognition probes targeting cell surface proteins such as aptamers play crucial roles in precise diagnostics and therapy. However, the selection of aptamers against low-abundance proteins in situ on the cell surface, especially in scarce samples, remains an unmet challenge. In this study, we present a single-round, single-cell aptamer selection method by employing a digital DNA sequencing strategy, termed DiDS selection, to address this dilemma. This approach incorporates a molecular identification card for each DNA template, thereby mitigating biases introduced by multiple PCR amplifications and ensuring the accurate identification of aptamer candidates. Through DiDS selection, we successfully obtained a series of high-quality aptamers against cell lines, clinical specimens, and neurons. Subsequent analyses for target identification revealed that aptamers derived from DiDS selection exhibit recognition capabilities for proteins with varying abundance levels. In contrast, multiple rounds of selection resulted in the enrichment of only one aptamer targeting a high-abundance target. Moreover, the comprehensive profiling of cell surfaces at the single-cell level, utilizing an enriched aptamer pool, revealed unique molecular patterns for each cell line. This streamlined approach holds promise for the rapid generation of specific recognition molecules targeting cell surface proteins across a broad range of expression levels and expands its applications in cell profiling, specific probe identification, biomarker discovery, etc.

Biomimetic Bacterial Capsule for Enhanced Aptamer Display and Cell Recognition.

Great effort has been made to encapsulate or coat living mammalian cells for a variety of applications ranging from diabetes treatment to three-dimensional printing. However, no study has reported the synthesis of a biomimetic bacterial capsule to display high-affinity aptamers on the cell surface for enhanced cell recognition. Therefore, we synthesized an ultrathin alginate-polylysine coating to display aptamers on the surface of living cells with natural killer (NK) cells as a model. The results show that this coating-mediated aptamer display is more stable than direct cholesterol insertion into the lipid bilayer. The half-life of the aptamer on the cell surface can be increased from less than 1.5 to over 20 h. NK cells coated with the biomimetic bacterial capsule exhibit a high efficiency in recognizing and killing target cells. Therefore, this work has demonstrated a promising cell coating method for the display of aptamers for enhanced cell recognition.

Screening of Cross-Reactive Aptamers for the Detection of 24 Quinolones by Using a Liebig's Law-Guided Parallel-Series Strategy.

Quinolones, a widely used class of antibiotics, present significant environmental and health concerns if they excessively remain in the environment and in food. Aptamers specific to quinolones can be applied as bioreceptors for the detection of quinolone residues in the environment and food. The quinolone family contains dozens of different individuals that share the same core structure coupled with various substituents at six different positions. The diversity and complexity of the substitution sites make it a challenge to choose a set of representative molecules that encompass all the desired sites and preserve the core molecular framework for the screening of quinolone-specific aptamers via systematic evolution of ligands by exponential enrichment (SELEX). To address this challenge, we introduce a novel parallel-series strategy guided by Liebig's law for isolating quinolone-specific cross-reactive aptamers by using the library-immobilized SELEX method. Through this approach, we successfully identified 5 aptamers (Apt.AQ01-Apt.AQ05) with high binding affinity and excellent specificity to 24 different quinolone individuals. Among them, Apt.AQ03 showcased optimal performance with affinities ranging from 0.14 to 1.07 µM across the comprehensive set of 24 quinolones, exhibiting excellent specificity against nontarget interferents. The binding performance of Apt.AQ03 was further characterized with microscale thermophoresis, circular dichroism spectra, and an exonuclease digestion assay. By using Apt.AQ03 as a bioreceptor, a fluorescence resonance energy transfer (FRET) aptasensor was developed for the detection of 24 quinolones in milk, achieving a remarkable detection limit of 14.5-21.8 ng/mL. This work not only establishes a robust and effective strategy for selecting cross-reactive aptamers applicable to other small-molecule families but also provides high-quality aptamers for developing various high-throughput and reliable methods for the detection of multiple quinolone residues in food.

Streamlining RNA Aptamer Selection via Unique Molecular Identifiers and High-Throughput Sequencing.

Aptamers are valuable tools for applications such as cell imaging, drug delivery, and therapeutics. RNA aptamers, in particular, exhibit complex structural diversity and flexibility, affording higher affinity and specificity, broader target recognition, and easier chemical modification compared with DNA aptamers. However, traditional selection methods for RNA aptamers are time-consuming and involve numerous rounds of screening, thus limiting their widespread application. To overcome this challenge, we propose an efficient truncated selection approach termed ID-SELEX. This method incorporates a molecular identification marker whereby each template is labeled with a unique molecular identifier, or UMI. Such incorporation helps mitigate biases introduced by multiple polymerase chain reaction (PCR) amplification during high-throughput sequencing, ensuring accurate identification of aptamer candidates. Utilizing ID-SELEX, we successfully identified a panel of high-quality aptamers targeting the human colon cancer cell line HCT-8 in just 2 rounds of selection. Furthermore, we demonstrated the versatility of this strategy by selecting 6 RNA aptamers targeting mouse myoblast cell line C2C12 with only one round of selection. In summary, RNA aptamer selection based on ID-SELEX utilizes high-throughput sequencing and UMI labeling to enable the rapid screening of RNA aptamers across human and murine cell lines. As such, ID-SELEX has the potential to facilitate RNA aptamer discovery, providing a novel molecular tool for biomedical research, clinical applications, and precision medicine.

In Silico Study on a Binding Mechanism of ssDNA Aptamers Targeting Glycosidic Bond-Containing Small Molecules.

Aptamer-based detection targeting glycoconjugates has attracted significant attention for its remarkable potential in identifying structural changes in saccharides in different stages of various diseases. However, the challenges in screening aptamers for small carbohydrates or glycoconjugates, which contain highly flexible and diverse glycosidic bonds, have hindered their application and commercialization. In this study, we investigated the binding conformations between three glycosidic bond-containing small molecules (GlySMs; glucose, N-acetylneuraminic acid, and neomycin) and their corresponding aptamers in silico, and analyzed factors contributing to their binding affinities. Based on the findings, a novel binding mechanism was proposed, highlighting the central role of the stem structure of the aptamer in binding and recognizing GlySMs and the auxiliary role of the mismatched bases in the adjacent loop. Guided by this binding mechanism, an aptamer with a higher 6'-sialyllactose binding affinity was designed, achieving a KD value of 4.54 ± 0.64 µM in vitro through a single shear and one mutation. The binding mechanism offers crucial guidance for designing high-affinity aptamers, enhancing the virtual screening efficiency for GlySMs. This streamlined workflow filters out ineffective binding sites, accelerating aptamer development and providing novel insights into glycan-nucleic acid interactions.