Mechanistic Inferences From Analysis of Measurements of Protein Phase Transitions in Live Cells. Issue 12 (11th June 2021) - Posey, Ammon E.; Ruff, Kiersten M.; Lalmansingh, Jared M.; Kandola, Tejbir S.; Lange, Jeffrey J.; Halfmann, Randal; Pappu, Rohit V.
Graphical abstract: Highlights: Automated methods for classifying and analyzing protein phase transitions are needed. DAmFRET is a high-throughput technique to study phase transitions in live cells. We introduce an automated method to classify phase transitions measured by DAmFRET. Discontinuous two-state transitions are quantified using classical nucleation theory. Our large-scale automated analysis of phase transitions yields mechanistic insights. Abstract: The combination of phase separation and disorder-to-order transitions can give rise to ordered, semi-crystalline fibrillar assemblies that underlie prion phenomena namely, the non-Mendelian transfer of information across cells. Recently, a method known as Distributed Amphifluoric Förster Resonance Energy Transfer (DAmFRET) was developed to study the convolution of phase separation and disorder-to-order transitions in live cells. In this assay, a protein of interest is expressed to a broad range of concentrations and the acquisition of local density and order, measured by changes in FRET, is used to map phase transitions for different proteins. The high-throughput nature of this assay affords the promise of uncovering sequence-to-phase behavior relationships in live cells. Here, we report the development of a supervised method to obtain automated and accurate classifications of phase transitions quantified using the DAmFRET assay. Systems that we classify as undergoing two-state discontinuous transitions are consistent with prion-like behaviors, although the converse is not always true. We uncover well-established and surprising new sequence features that contribute to two-state phase behavior of prion-like domains. Additionally, our method enables quantitative, comparative assessments of sequence-specific driving forces for phase transitions in live cells. Finally, we demonstrate that a modest augmentation of DAmFRET measurements, specifically time-dependent protein expression profiles, can allow one to apply classical nucleation theory to extract sequence-specific lower bounds on the probability of nucleating ordered assemblies. Taken together, our approaches lead to a useful analysis pipeline that enables the extraction of mechanistic inferences regarding phase transitions in live cells.