Project description
Compartmentalization plays a crucial role in early life, facilitating the emergence of complex life forms from simple prebiotic reaction networks. In prokaryotic cells and primitive protocells, spatial division by membranes is not present. Instead, compartmentalization is enabled through the process of phase separation of RNA-protein systems, forming distinct liquid-like droplets, also known as biological condensates. Eukaryotic cells use phase condensation in both nucleus and cytoplasm to provide spatiotemporal organization and to catalyze biochemical reactions. Understanding how RNA-protein interactions drive this process will not only illuminate early life conditions but also provide insights into the fundamental principles of biological organization and function in life and disease.
RNA-protein interactions play key roles in gene expression through the formation of stress granules and P-bodies in mRNA metabolism and the formation of transcriptional condensates at the chromosome. RNA-protein condensates also regulate selective signaling pathways by concentrating specific clients and substrates. At the same time, aberrant phase separation can lead to pathological aggregation in neurodegenerative diseases, can contribute to cancer progression by driving oncogenic transcriptional programs and can facilitate viral infection by viruses hijacking cellular condensates to facilitate replication.
Despite the crucial role of RNA-protein condensates in cellular organization and disease pathogenesis, a full understanding of the underlying RNA-protein interactions is lacking. Here, we will use coarse-grained molecular dynamics at single amino acid and nucleotide resolution to provide a mechanistic understanding of the key molecular driving forces for condensate formation and function. We aim to explore the effect of RNA and protein sequence, secondary structure and relative stoichiometries on phase condensation and resolve the out-of-equilibrium selective partitioning and segregation of specific cellular functions. Our results are not only expected to lead to new insights on RNA-protein compartmentalization in primitive life, but will also contribute to fundamental insights on biological condensate formation, function and pathology.
Additional specifications
We look for a candidate with a master degree in (bio)physics, (bio)chemistry or a related field, with a strong interest in computational modelling. The project will entail programming (scripting, Python etc.), handling big data and carrying out all-atom and coarse-grained molecular dynamics simulations on high-performance super-computers.
