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Decoding the thermodynamics of multi-component biomolecular condensates using high-throughput combinatorial microfluidics-based approaches

Many biomolecules in the cell, especially proteins and nucleic acids, remain spatiotemporally organized as concentrated dynamic assemblies, commonly referred to as biomolecular condensates. The formation of biomolecular condensates has emerged as an important principle for the organisation of cellular structure and biochemistry across all forms of life. Multiple natural condensates such as p-bodies or stress granules contain many components that are linked by large-scale weak multivalent interactions. There is growing evidence that the formation of many (but not all) biomolecular condensates involves liquid-liquid phase separation. The fundamental physicochemical principles underlying the formation of multi-component biomolecular condensates remain poorly understood. There is limited understanding of how different constituents contribute to the energetics of assembly of biomolecular condensates, whether they act cooperatively or independently of each other, and whether the energetic behaviors can be inferred from known connectivities or evolutionary relationships between the molecules. It is essential to study the energetics of interactions within condensates to understand the molecular underpinnings of their macroscopic behaviour.  This requires mapping of phase space of the condensates, which is a two-dimensional array of points for a two-component system and extends to being a n-dimensional array for a system consisting of n-components. Unfortunately, the traditional methods used for mapping phase diagrams require substantial amounts of reagents and are labour intensive. Hence, I propose to develop a high-throughput microfluidics-based platform in which millions of small volume (pL) droplets can be made and analysed as individual mini reaction chambers, providing information about millions of points in the phase space for any give condensate in a single experiment. With this method, I eventually plan to map multi-dimensional phase diagrams for natural biomolecular condensates, in-vitro. This will facilitate the understanding of protein interaction networks in the biomolecular condensates and will also allow for the delineation of the combinatorial complexity of potential epistatic interactions in multi-component systems.


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