Gullerova Lab

Genetic information stored in DNA is continuously exposed to endogenous or exogenous damaging factors. Efficient DNA damage repair is a fundamental process for every living organism. The accumulation of DNA damage affects cellular viability and leads to a variety of diseases, particularly cancer. Therefore, understanding of the molecular mechanisms necessary for DNA damage repair is of great importance. A myriad of repair factors targets double-strand breaks (DSBs) by non-homologous end joining (NHEJ) or homologous recombination (HR) pathways. However, the relevance of RNA for the DNA damage response (DDR) is currently not understood and the impact of transcription on genome stability and the role of RNA binding factors as well as function of small RNA (DDRNA) remain enigmatic. My research aims to elucidate molecular mechanism of RNA dependent DDR and its relevance to cancer. We pay special attention to various types of small non-coding RNA and their roles within DDR pathway as well as acting signalling molecules. We study RNA dependent DDR on four main levels: regulation of transcription, RNA modifications and processing, functional roles of damage derived RNA and RNA binding proteins.

With the rapid development of deep learning, its integration into drug repurposing has become a prominent area of research. Advanced AI techniques are increasingly used for feature extraction and model construction, with a growing trend towards this approach. While most current methods focus on screening interactions between proteins and small-molecule drugs, there are limited methods available for large-scale screening of RNA-small molecule drug interactions. To address this gap, we are developing a state-of-the-art AI-based drug repurposing system specifically designed for RNA ligands. We have developed an advanced multimodal feature embedding extraction and comparison platform that leverages a variety of features, including sequence and structure. Our approach employs deep learning model construction and validation using multiple feature extraction techniques based on natural language processing, computer vision, and complex graph networks, achieving state-of-the-art model performance. Our system is capable of conducting large-scale drug screening and prediction for any RNA in a short period.The platform integrates and facilitates interactions between in silico experiments and wet lab experiments. Predictions made by in silico experiments are validated through wet lab experiments. Feedback from wet lab experiments is used to retrain the model and improve the screening process. The system is highly scalable, allowing for the introduction of new embeddings and datasets, ensuring continuous improvement and adaptability.

Mammalian cells employ small RNAs (sRNAs) molecules to regulate gene expression in a pathway known as RNA interference (RNAi). Transfer RNAs (tRNAs) are essential for translation but also serve as a source for tRNA-derived small RNAs (tsRNAs). We discovered that the endoribonuclease Dicer, a critical player in canonical RNAi, associates with actively transcribed tRNA genes, binds to alternatively folded tRNAs and processes them into tsRNAs. Dicer-dependent tsRNAs target the introns of many protein coding genes and long non-coding RNAs, leading to degradation of their nascent RNA. Importantly, tsRNAs target genes are significantly associated with disease phenotypes underpinning the biological importance of this pathway. We discovered a mechanism for intronic gene silencing that is distinct from well-known post-transcriptional or transcriptional gene expression regulation. We employ synthetic tsRNA targeting oncogenes to suppress aggressive cancer phenotype, which has promising applications in future cancer therapies (patents filed by Cancer Research UK). We wish to understand why and how is intronic gene silencing de-regulated in cancer cells and what is the potency of using synthetic tsRNA in cancer cells in order to suppress their oncogenic phenotype. Furthermore, we found that another class of small RNA: vault RNA derived small RNA can also mediate nascent RNA silencing and modulate expression of membrane-associated genes. We are interested to understand how RNAP III transcripts (tRNA or vtRNA) can serve as Dicer substrates and what else regulates tsRNA/svtRNA biogenesis.