In vitro Selection of High Affinity DNA and RNA Aptamers that Detect Hepatitis C Virus Core Protein of Genotypes 1 to 4 and Inhibit Virus Production in Cell Culture.

Hepatitis C virus (HCV) core is a highly conserved and multifunctional protein that forms the viral capsid, making it an attractive target for HCV detection and inhibition. Aptamers are in vitro selected, single-stranded nucleic acids (RNA or ssDNA) with growing applicability in viral diagnostics and therapy. We have carried out DNA and RNA in vitro selection against six different variants of HCV core protein: two versions of the full-length protein of genotype 1, and the hydrophilic domain of genotypes 1 to 4. The aptamer populations obtained were analyzed by means of Ultra-Deep Sequencing (UDS), the most abundant sequences were identified and a number of highly represented sequence motifs were unveiled. Affinity (measured as the dissociation constant, Kd) of the most abundant DNA and RNA aptamers were quantified using Enzyme-Linked OligoNucleotide Assay (ELONA)-based methods. Some aptamers with nanomolar or subnanomolar Kd values (as low as 0.4 nM) were the common outcome of DNA and RNA selections against different HCV core variants. They were tested in sandwich and competitive biosensor assays, reaching a limit of detection for HCV core of 2 pM. Additionally, the two most prevalent and high affinity aptamers were assayed in Huh-7.5 reporter cell lines infected with HCV, where they decreased both the viral progeny titer and the extracellular viral RNA level, while increasing the amount of intracellular viral RNA. Our results suggest that these aptamers inhibit HCV capsid assembly and virion formation, thus making them good candidate molecules for the design of novel therapeutic approaches for hepatitis C.

A Combined ELONA-(RT)qPCR Approach for Characterizing DNA and RNA Aptamers Selected against PCBP-2.

Improvements in Systematic Evolution of Ligands by EXponential enrichment (SELEX) technology and DNA sequencing methods have led to the identification of a large number of active nucleic acid molecules after any aptamer selection experiment. As a result, the search for the fittest aptamers has become a laborious and time-consuming task. Herein, we present an optimized approach for the label-free characterization of DNA and RNA aptamers in parallel. The developed method consists in an Enzyme-Linked OligoNucleotide Assay (ELONA) coupled to either real-time quantitative PCR (qPCR, for DNA aptamers) or reverse transcription qPCR (RTqPCR, for RNA aptamers), which allows the detection of aptamer-target interactions in the high femtomolar range. We have applied this methodology to the affinity analysis of DNA and RNA aptamers selected against the poly(C)-binding protein 2 (PCBP-2). In addition, we have used ELONA-(RT)qPCR to quantify the dissociation constant (Kd) and maximum binding capacity (Bmax) of 16 high affinity DNA and RNA aptamers. The Kd values of the high affinity DNA aptamers were compared to those derived from colorimetric ELONA performed in parallel. Additionally, Electrophoretic Mobility Shift Assays (EMSA) were used to confirm the binding of representative PCBP-2-specific RNA aptamers in solution. We propose this ELONA-(RT)qPCR approach as a general strategy for aptamer characterization, with a broad applicability in biotechnology and biomedicine.

An Efficient Microarray-Based Genotyping Platform for the Identification of Drug-Resistance Mutations in Majority and Minority Subpopulations of HIV-1 Quasispecies.

The response of human immunodeficiency virus type 1 (HIV-1) quasispecies to antiretroviral therapy is influenced by the ensemble of mutants that composes the evolving population. Low-abundance subpopulations within HIV-1 quasispecies may determine the viral response to the administered drug combinations. However, routine sequencing assays available to clinical laboratories do not recognize HIV-1 minority variants representing less than 25% of the population. Although several alternative and more sensitive genotyping techniques have been developed, including next-generation sequencing (NGS) methods, they are usually very time consuming, expensive and require highly trained personnel, thus becoming unrealistic approaches in daily clinical practice. Here we describe the development and testing of a HIV-1 genotyping DNA microarray that detects and quantifies, in majority and minority viral subpopulations, relevant mutations and amino acid insertions in 42 codons of the pol gene associated with drug- and multidrug-resistance to protease (PR) and reverse transcriptase (RT) inhibitors. A customized bioinformatics protocol has been implemented to analyze the microarray hybridization data by including a new normalization procedure and a stepwise filtering algorithm, which resulted in the highly accurate (96.33%) detection of positive/negative signals. This microarray has been tested with 57 subtype B HIV-1 clinical samples extracted from multi-treated patients, showing an overall identification of 95.53% and 89.24% of the queried PR and RT codons, respectively, and enough sensitivity to detect minority subpopulations representing as low as 5-10% of the total quasispecies. The developed genotyping platform represents an efficient diagnostic and prognostic tool useful to personalize antiviral treatments in clinical practice.