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Next-generation systematic evolution of ligands by exponential enrichment approaches consistently combine the experimental protocol with high-throughput sequencing after each round of selection. This extension, known as HT-SELEX, results in a vast amount of raw sequencing data that requires tailored bioinformatics approaches to efficiently process and analyze these reads. Here, we present a step-by-step walkthrough of AptaSUITE, a previously published, open-source, and platform-independent software collection of peer-reviewed bioinformatics tools for HT-SELEX data, integrated into a convenient and efficient graphical user interface. We highlight AptaSUITE's main components and illustrate their utility for a variety of usage scenarios. These include, but are not limited to, computational solutions for data preprocessing such as demultiplexing and quality control, aptamer candidate identification, as well as binding motif elucidation. Taken together, AptaSUITE comprises a complete bioinformatics solution for HT-SELEX data analysis while providing real-time, intuitive, and graphical access to the aptamer information., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Understanding the principles of DNA binding by transcription factors (TFs) is of primary importance for studying gene regulation. Recently, several lines of evidence suggested that both DNA sequence and shape contribute to TF binding. However, the following compelling question is yet to be considered: in the absence of any sequence similarity to the binding motif, can DNA shape still increase binding probability? To address this challenge, we developed Co-SELECT, a computational approach to analyze the results of in vitro HT-SELEX experiments for TF-DNA binding. Specifically, Co-SELECT leverages the presence of motif-free sequences in late HT-SELEX rounds and their enrichment in weak binders allows Co-SELECT to detect an evidence for the role of DNA shape features in TF binding. Our approach revealed that, even in the absence of the sequence motif, TFs have propensity to bind to DNA molecules of the shape consistent with the motif specific binding. This provides the first direct evidence that shape features that accompany the preferred sequence motifs also bestow an advantage for weak, sequence non-specific binding., (Published by Oxford University Press on behalf of Nucleic Acids Research 2019.)

RNA-based therapeutics, i.e. the utilization of synthetic RNA molecules to alter cellular functions, have the potential to address targets which are currently out of scope for traditional drug design pipelines. This potential however hinges on the ability to selectively deliver and internalize therapeutic RNAs into cells of interest. Cell internalizing RNA aptamers selected against surface receptors and discriminatively expressed on target cells hold particular promise as suitable candidates for such delivery agents. Specifically, these aptamers can be combined with a therapeutic cargo and facilitate internalization of the cargo into the cell of interest. A recently proposed method to obtain such aptamer-cargo constructs employs a double-stranded "sticky bridge" where the complementary strands constituting the bridge are conjugated with the aptamer and the cargo respectively. The design of appropriate sticky bridge sequences however has proven highly challenging given the structural and functional constraints imposed on them during synthesis and administration. These include, but are not limited to, guaranteed formation and stability of the complex, non-interference with the aptamer or the cargo, as well as the prevention of spurious aggregation of the molecules during incubation. In order to address these issues, we have developed AptaBlocks - a computational method to design RNA complexes that hybridize via sticky bridges. The effectiveness of our approach has been verified computationally, and experimentally in the context of drug delivery to pancreatic cancer cells. Importantly, AptaBlocks is a general method for the assembly of nucleic acid systems that, in addition to designing of RNA-based drug delivery systems, can be used in other applications of RNA nanotechnology. AptaBlocks is available at https://github.com/wyjhxq/AptaBlocks.

Aptamers, short and synthetic RNA/DNA molecules binding distinct targets with high affinity and specificity, are identified via Systematic Evolution of Ligands by Exponential Enrichment (SELEX), an in vitro procedure that, starting from a pool of random ssDNA/RNA sequences, selects sequences by amplifying target-affine species through a series of selection cycles. This versatile protocol has recently been combined with high throughput sequencing, allowing arbitrary stages of the selection to be sequenced and analyzed in silico. As a prerequisite, these data require extensive preprocessing by means of quality controls, error correction and demultiplexing, all while taking into account the specific design of aptamers. Existing solutions addressing this task are currently present only as integrated components in larger pipelines, limiting their applicability in independent software solutions. Here we present AptaPLEX, a standalone and platform independent demultiplexer specifically designed for HT-SELEX data. Given the multiplexed data from one or multiple HT-SELEX experiments, AptaPLEX extracts and restores aptamers into the original selection cycles by identifying the barcode and primer regions in each read. AptaPLEX is capable of fuzzy matching for both the barcode and primers, and automatically corrects mismatches between forward and reverse reads for paired-end data. Our software provides a rich set of additional features and can easily be integrated into existing analysis automation pipelines on multiple platforms ranging from desktop machines to cloud based solutions., (Copyright © 2016. Published by Elsevier Inc.)

Oligonucleotide aptamers represent a novel platform for creating ligands with desired specificity, and they offer many potentially significant advantages over monoclonal antibodies in terms of feasibility, cost, and clinical applicability. However, the isolation of high-affinity aptamer ligands from random oligonucleotide pools has been challenging. Although high-throughput sequencing (HTS) promises to significantly facilitate systematic evolution of ligands by exponential enrichment (SELEX) analysis, the enormous datasets generated in the process pose new challenges for identifying those rare, high-affinity aptamers present in a given pool. We show that emulsion PCR preserves library diversity, preventing the loss of rare high-affinity aptamers that are difficult to amplify. We also demonstrate the importance of using reference targets to eliminate binding candidates with reduced specificity. Using a combination of bioinformatics and functional analyses, we show that the rate of amplification is more predictive than prevalence with respect to binding affinity and that the mutational landscape within a cluster of related aptamers can guide the identification of high-affinity aptamer ligands. Finally, we demonstrate the power of this selection process for identifying cross-species aptamers that can bind human receptors and cross-react with their murine orthologs., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Motivation: Systematic Evolution of Ligands by EXponential Enrichment (SELEX) represents a state-of-the-art technology to isolate single-stranded (ribo)nucleic acid fragments, named aptamers, which bind to a molecule (or molecules) of interest via specific structural regions induced by their sequence-dependent fold. This powerful method has applications in designing protein inhibitors, molecular detection systems, therapeutic drugs and antibody replacement among others. However, full understanding and consequently optimal utilization of the process has lagged behind its wide application due to the lack of dedicated computational approaches. At the same time, the combination of SELEX with novel sequencing technologies is beginning to provide the data that will allow the examination of a variety of properties of the selection process., Results: To close this gap we developed, Aptamotif, a computational method for the identification of sequence-structure motifs in SELEX-derived aptamers. To increase the chances of identifying functional motifs, Aptamotif uses an ensemble-based approach. We validated the method using two published aptamer datasets containing experimentally determined motifs of increasing complexity. We were able to recreate the author's findings to a high degree, thus proving the capability of our approach to identify binding motifs in SELEX data. Additionally, using our new experimental dataset, we illustrate the application of Aptamotif to elucidate several properties of the selection process.