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Using quantitative reconstitution to investigate multi-component condensates.

Simon L CurrieMichael K Rosen
Published in: RNA (New York, N.Y.) (2021)
Many biomolecular condensates are thought to form via liquid-liquid phase separation (LLPS) of multivalent macromolecules. For those that form through this mechanism, our understanding has benefitted significantly from biochemical reconstitutions of key components and activities. Reconstitutions of RNA-based condensates to date have mostly been based on relatively simple collections of molecules. However, proteomics and sequencing data indicate that natural RNA-based condensates are enriched in hundreds to thousands of different components, and genetic data suggest multiple interactions can contribute to condensate formation to varying degrees. In this perspective we describe recent progress in understanding RNA-based condensates through different levels of biochemical reconstitutions, as a means to bridge the gap between simple in vitro reconstitution and cellular analyses. Complex reconstitutions provide insight into the formation, regulation, and functions of multi-component condensates. We focus on two RNA-protein condensate case studies: stress granules and RNA processing bodies (P bodies), and examine the evidence for cooperative interactions among multiple components promoting LLPS. An important concept emerging from these studies is that composition and stoichiometry regulate biochemical activities within condensates. Based on the lessons learned from stress granules and P bodies we discuss forward-looking approaches to understand the thermodynamic relationships between condensate components, with the goal of developing predictive models of composition and material properties, and their effects on biochemical activities. We anticipate that quantitative reconstitutions will facilitate understanding of the complex thermodynamics and functions of diverse RNA-protein condensates.
Keyphrases
  • electronic health record
  • mass spectrometry
  • stress induced
  • dna methylation
  • single cell
  • amino acid
  • label free