Biology subjects

Wengel, J.

Publications and source records attributed to Wengel, J..

3 recordsLinked to original sources

bioRxiv2025

Lock, Protect, and Bind: In Vitro Selection of LNA-modified Aptamers Using a Mutant T7 RNA Polymerase

RNA therapeutics are powerful tools for gene modulation and targeted therapies, but their clinical application is hindered by nuclease degradation and immunogenicity. Incorporating chemical modifications, like locked nucleic acids (LNAs), can enhance nuclease resistance, targeting properties, and thermal stability. Traditionally, LNA incorporation has relied on solid-phase synthesis of short RNAs. Engineered polymerases capable of incorporating xenonucleic acids (XNAs), including LNA, into longer RNAs have been described. However, their XNA yield is limited by primer and template copy numbers, and the generated DNA-XNA duplexes can be difficult to purify. We present a novel approach for incorporating LNA-ATP and LNA-TTP alongside 2Fluoro (2F)-modified pyrimidines via in vitro transcription using a mutant T7 RNA polymerase. This method enables efficient, primer-independent synthesis and amplification of LNA-modified RNA with low error rates. To demonstrate its utility, we performed in vitro selection (SELEX) of LNA- and 2F-modified aptamers targeting Influenza hemagglutinin (HA) and human CD40 ligand (hCD40L), two therapeutically relevant proteins. Iterative SELEX cycles yielded aptamers with low-nanomolar affinities, high specificity, and high nuclease resistance. Overall, this approach provides a scalable and versatile platform for generating chemically stabilized RNAs, fully compatible with SELEX, and holds potential for developing next-generation RNA-based therapeutics with improved pharmacokinetics.

molecular biology↗

bioRxiv2024

Anti-gene oligonucleotides targeting Friedreichs ataxia expanded GAA:TTC repeats increase Frataxin expression

Friedreichs ataxia (FRDA) is a progressive, autosomal recessive ataxia caused, in the majority of cases, by homozygous expansion of GAA*TTC triplet-repeats in the first intron of the frataxin (FXN) gene. GAA*TTC repeat expansion results in the formation of non-B DNA intramolecular triplex structure (H-DNA) as well as changes in the epigenetic landscape at FXN loci and heterochromatin formation. Expansion of intronic GAA*TTC repeats is associated with reduced levels of FXN mRNA and protein resulting in disease development. Previously, we reported that DNA-binding anti-gene oligonucleotides (AGOs) targeting the GAA*TTC repeat expansion abolished H-DNA formation. Here, we demonstrate that targeting repeat-expanded chromosomal DNA using single-strand locked nucleic acid (LNA)-DNA mixmer AGOs increases FXN mRNA and protein expression in patient-derived cells. We examined numerous LNA-DNA AGOs and found that the design, length and their LNA composition have a high impact on the effectiveness of the treatment. Collectively, our results demonstrate the unique capability of specifically designed ONs targeting the GAA*TTC DNA repeats to upregulate FXN gene expression.

molecular biology↗

bioRxiv2023

AptaBERT: Predicting aptamer binding interactions

AO_SCPLOWBSTRACTC_SCPLOWAptamers, short single-stranded DNA or RNA, are promising as future diagnostic and therapeutic agents. Traditional selection methods, such as the Systemic Evolution of Ligands by Exponential Enrichment (SELEX), are not without limitations being both resource-intensive and prone to biases in library construction and the selection phase. Leveraging Dianoxs extensive aptamer database, we introduce a novel computational approach, AptaBERT, built upon the BERT architecture. This method utilizes self-supervised pre-training on vast amounts of data, followed by supervised fine-tuning to enhance the prediction of aptamer interactions with proteins and small molecules. AptaBERT is fine-tuned for binary classification tasks, distinguishing between positive and negative interactions with proteins and small molecules. AptaBERT achieves a ROC-AUC of 96% for protein interactions, surpassing existing models by at least 15%. For small molecule interactions, AptaBERT attains an ROC-AUC of 85%. Our findings demonstrate AptaBERTs superior predictive capability and its potential to identify novel aptamers binding to targets.

bioinformatics↗