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© 2020 Elsevier Ltd Protein phase transitions are particularly amenable for cell signalling as these highly cooperative processes allow cells to make binary decisions in response to relatively small intracellular changes. The different processes of condensate formation and the distinct material properties of the resulting condensates provide a dictionary to modulate a range of decisions on cell fate. We argue that, on the one hand, the reversibility of liquid demixing offers a chance to arrest cell growth under specific circumstances. On the other hand, the transition to amyloids is better suited for terminal decisions such as those leading to apoptosis and necrosis. Here, we review recent examples of both scenarios, highlighting how mutations in signalling proteins affect the formation of biomolecular condensates with drastic effects on cell survival.

JTD Keywords: amyloid, cell death, deep mutagenesis, llps, rna-binding proteins, Amyloid, Cell death, Deep mutagenesis, Llps, Phase transition, Proteins, Rna-binding proteins, Signal transduction

Plaques of the amyloid beta (A beta) peptide are a pathological hallmark of Alzheimer's disease (AD), the most common form of dementia. Mutations in A beta also cause familial forms of AD (fAD). Here, we use deep mutational scanning to quantify the effects of >14,000 mutations on the aggregation of A beta. The resulting genetic landscape reveals mechanistic insights into fibril nucleation, including the importance of charge and gatekeeper residues in the disordered region outside of the amyloid core in preventing nucleation. Strikingly, unlike computational predictors and previous measurements, the empirical nucleation scores accurately identify all known dominant fAD mutations in A beta, genetically validating that the mechanism of nucleation in a cell-based assay is likely to be very similar to the mechanism that causes the human disease. These results provide the first comprehensive atlas of how mutations alter the formation of any amyloid fibril and a resource for the interpretation of genetic variation in A beta.

JTD Keywords: aggregation, kinetics, oligomers, onset, rates, state, Aggregation, Alzheimer disease, Alzheimer's, Amyloid, Amyloid beta-peptides, Computational biology, Deep mutagenesis, Dna mutational analysis, Genetics, Genomics, High-throughput nucleotide sequencing, Kinetics, Mutation, Nucleation, Oligomers, Onset, Plasmids, Precursor protein, Rates, S. cerevisiae, Saccharomyces cerevisiae, State, Systems biology