In the NWO Open Competition ENW-XS, 56 proposals have been awarded funding, including five projects by Radboud researchers. The grants of up to €50,000 are intended for promising, innovative, and high-risk research ideas within the exact and natural sciences. These concern groundbreaking research where the outcome is not predetermined, but where any result, positive or negative, advances science.
Uncovering the molecular origin of synapse dysfunction in Alzheimer’s Disease
Wouter Droogers (Donders Centre for Neuroscience, Radboud Universiteit)
Dysfunction and degeneration of synapses leads to an imbalance between excitation and inhibition in the brain in many neurological disorders, including Alzheimer’s Disease. Finding the molecular origin of what makes synapses vulnerable or resilient is key to finding new cures and restoring the excitation-inhibition balance. Here, we aim to identify the cause of synaptic dysfunction by detecting more than a thousand mRNA molecules in millions of synapses during the progression of Alzheimer’s Disease. This will enable us to find new therapeutic targets that can salvage synaptic function and restore the excitation-inhibition balance in early stages of Alzheimer’s Disease.
Identifying small molecules that prevent drug tolerant persisters
Maike Hansen (Institute for Molecules and Materials, Radboud Universiteit)
Cancer treatments often fail because a small fraction of cancer cells can temporarily survive therapy by entering a drug-tolerant state. Some of these cells can reduce protein production to withstand treatment and later give rise to permanent resistance. This project aims to identify small molecules that prevent cancer cells from entering, or help them exit, this tolerant state by maintaining normal protein production. By targeting this early, reversible phase of drug resistance, the project seeks to block resistance before it develops, opening new avenues for more durable and effective cancer therapies.
Eating the Enemy: Biofilm-powered Nanomotors as a new Antimicrobial strategy
Veerpal Kaur (Radboud Universiteit)
Antibiotic-resistant infections are a growing global threat, often caused by bacterial biofilms, dense communities of bacteria protected by a sticky matrix. These biofilms are extremely hard to treat because medicines cannot reach the bacteria inside. Our project develops tiny, biodegradable “nanomotors” that move through the biofilm by using it as fuel. As they travel, they break down the protective matrix and release antimicrobial agents directly where bacteria hide. This approach turns the bacteria’s defence against themselves, offering a precise, efficient way to treat stubborn infections and reduce reliance on traditional antibiotics.
Data-driven mapping of lipopeptide antibiotic activity for targeted drug design
Mathijs Mabesoone (Institute for Molecules and Materials, Radboud Universiteit)
We urgently need new drugs to combat the rising microbial resistance against clinically used antibiotics. Peptides have emerged as a promising new scaffold for antibiotics development, and AI models have been developed that promise to accelerate this development. However, the antimicrobial peptides these AI models suggest, lack important modifications and suffer from poor drug stability, resulting in little clinical impact. Leveraging our recently established ability to produce large libraries of modified peptides, we propose a data-driven strategy to obtain AI models that predict antimicrobial activity of lipopeptides. These AI models can enable targeted design of promising, pharmacologically relevant antimicrobial peptides.
A multi-modal approach to explore RNA methylation and hormonal crosstalk in early human development
Klaas Mulder (RIMLS-Science, Radboud Universiteit)
In the earliest days of life, embryos must switch from using maternal instructions stored in the egg to activating their own genes. This transition relies on chemical “tags” on RNA, called methylation, that control whether messages are removed or kept. Using a human stem-cell based embryo model (blastoid), this project will explore how the hormone estrogen influences these RNA tags and RNA stability. By developing a novel workflow to measure these processes simultaneously, the project aims to improve the reliability of the blastoid model and provide insights that could eventually help improve the success of assisted reproduction.