Intracellular phase separation of proteins into biomolecular condensates is increasingly recognized as a process with a key role in cellular compartmentalization and regulation. Different hypotheses about the parameters that determine the tendency of proteins to form condensates have been proposed, with some of them probed experimentally through the use of constructs generated by sequence alterations. To broaden the scope of these observations, we established an in silico strategy for understanding on a global level the associations between protein sequence and phase behavior and further constructed machine-learning models for predicting protein liquid–liquid phase separation (LLPS). Our analysis highlighted that LLPS-prone proteins are more disordered, less hydrophobic, and of lower Shannon entropy than sequences in the Protein Data Bank or the Swiss-Prot database and that they show a fine balance in their relative content of polar and hydrophobic residues. To further learn in a hypothesis-free manner the sequence features underpinning LLPS, we trained a neural network-based language model and found that a classifier constructed on such embeddings learned the underlying principles of phase behavior at a comparable accuracy to a classifier that used knowledge-based features. By combining knowledge-based features with unsupervised embeddings, we generated an integrated model that distinguished LLPS-prone sequences both from structured proteins and from unstructured proteins with a lower LLPS propensity and further identified such sequences from the human proteome at a high accuracy. These results provide a platform rooted in molecular principles for understanding protein phase behavior. The predictor, termed DeePhase, is accessible from https://deephase.ch.cam.ac.uk/.

RNA viruses induce the formation of subcellular organelles that provide microenvironments conducive to their replication. Here we show that replication factories of rotaviruses represent protein-RNA condensates that are formed via liquid-liquid phase separation of the viroplasm-forming proteins NSP5 and rotavirus RNA chaperone NSP2. Upon mixing, these proteins readily form condensates at physiologically relevant low micromolar concentrations achieved in the cytoplasm of virus-infected cells. Early infection stage condensates could be reversibly dissolved by 1,6-hexanediol, as well as propylene glycol that released rotavirus transcripts from these condensates. During the early stages of infection, propylene glycol treatments reduced viral replication and phosphorylation of the condensate-forming protein NSP5. During late infection, these condensates exhibited altered material properties and became resistant to propylene glycol, coinciding with hyperphosphorylation of NSP5. Some aspects of the assembly of cytoplasmic rotavirus replication factories mirror the formation of other ribonucleoprotein granules. Such viral RNA-rich condensates that support replication of multi-segmented genomes represent an attractive target for developing novel therapeutic approaches.

The assembly of intracellular proteins into biomolecular condensates via liquid-liquid phase separation (LLPS) has emerged as a fundamental process underlying the organisation and regulation of cellular space and function. Physicochemical characterisation of the parameters that control and modulate phase separation is therefore essential for an improved understanding of protein phase behaviour, including for the therapeutic modulation of LLPS phenomena. A fundamental measure with which to describe protein phase behaviour in chemical space is the phase diagram. Characterisation of phase diagrams requires measuring the presence or absence of the condensed phase under a multitude of conditions and, as such, is associated with significant consumption of time and sample volume even when performed in microwell format.However, due to the rapidly increasing number of biologically and disease-relevant condensate systems, experimental techniques that enable high-throughput analysis of protein phase behaviour are required. To address this challenge, we present here a combinatorial droplet microfluidic platform, termed PhaseScan, for the rapid and high-resolution acquisition of protein phase diagrams. Using this platform, we demonstrate characterisation of the phase behaviour of a pathologically relevant mutant of the protein fused in sarcoma (FUS) in a highly parallelised manner, with significantly improved assay throughput and reduced sample consumption. We demonstrate the capability of the platform by finding the phase boundary at which FUS transitions from a one-phase to a two-phase state as modulated by 1,6-hexanediol, and estimate the free-energy landscape of this system using Flory-Huggins theory. These results thus provide a basis for the rapid acquisition of phase diagrams through the application of microdroplet techniques and pave the way for a wide range of applications, enabling rapid characterisation of the effect of environmental conditions and coacervate species on the thermodynamics of phase separation.

The assembly of biomolecules into condensates is a fundamental process underlying the organisation of the intracellular space and the regulation of many cellular functions. Mapping and characterising phase behaviour of biomolecules is essential to understand the mechanisms of condensate assembly, and to develop therapeutic strategies targeting biomolecular condensate systems. A central concept for characterising phase-separating systems is the phase diagram. Phase diagrams are typically built from numerous individual measurements sampling different parts of the parameter space. However, even when performed in microwell plate format, this process is slow, low throughput and requires significant sample consumption. To address this challenge, we present here a combinatorial droplet microfluidic platform, termed PhaseScan, for rapid and high-resolution acquisition of multidimensional biomolecular phase diagrams. Using this platform, we characterise the phase behaviour of a wide range of systems under a variety of conditions and demonstrate that this approach allows the quantitative characterisation of the effect of small molecules on biomolecular phase transitions.

Liquid–liquid phase‐separated biomolecular systems are increasingly recognized as key components in the intracellular milieu where they provide spatial organization to the cytoplasm and the nucleoplasm. The widespread use of phase‐separated systems by nature has given rise to the inspiration of engineering such functional systems in the laboratory. In particular, reversible gelation of liquid–liquid phase‐separated systems could confer functional advantages to the generation of new soft materials. Such gelation processes of biomolecular condensates have been extensively studied due to their links with disease. However, the inverse process, the gel–sol transition, has been less explored. Here, a thermoresponsive gel–sol transition of an extracellular protein in microgel form is explored, resulting in an all‐aqueous liquid–liquid phase‐separated system with high homogeneity. During this gel–sol transition, elongated gelatin microgels are demonstrated to be converted to a spherical geometry due to interfacial tension becoming the dominant energetic contribution as elasticity diminishes. The phase‐separated system is further explored with respect to the diffusion of small particles for drug‐release scenarios. Together, this all‐aqueous system opens up a route toward size‐tunable and monodisperse synthetic biomolecular condensates and controlled liquid–liquid interfaces, offering possibilities for applications in bioengineering and biomedicine.