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Membraneless organelles within the living cell use phase separation of biomolecules coupled with enzymatic reactions to regulate cellular processes. The diverse functions of these biomolecular condensates motivate the pursuit of simpler in vitro models that exhibit primitive forms of self-regulation based on internal feedback mechanisms. Here, we investigate one such model based on complex coacervation of the enzyme catalase with an oppositely charge polyelectrolyte DEAE-dextran to form pH-responsive catalytic droplets. Upon addition of hydrogen peroxide “fuel”, enzyme activity localized within the droplets causes a rapid increase in the pH. Under appropriate conditions, this reaction-induced pH change triggers coacervate dissolution owing to its pH-responsive phase behavior. Notably, this destabilizing effect of the enzymatic reaction on phase separation depends on droplet size owing to the diffusive delivery and removal of reaction components. Reaction-diffusion models informed by the experimental data show that larger drops support larger changes in the local pH thereby enhancing their dissolution relative to smaller droplets. Together, these results provide a basis for achieving droplet size control based on negative feedback between pH-dependent phase separation and pH-changing enzymatic reactions. 

Abstract Phase separation provides intracellular organization and underlies a variety of cellular processes. These biomolecular condensates exhibit distinct physical and material properties. Current strategies for engineering condensate formation include using intrinsically disordered domains and altering protein surface charge by chemical supercharging or site-specific mutagenesis. We propose adding to this toolbox designer peptide tags that provide several potential advantages for engineering protein phase separation in bacteria. Herein, we demonstrate the use of short cationic peptide tags for sequestration of proteins of interest into bacterial condensates and provide a foundational study for their development as tools for condensate engineering. Using a panel of GFP variants, we demonstrate how cationic tag and globular domain charge contribute to intracellular phase separation inE. coliand observe that the tag can affect condensate disassembly at a given net charge near the phase separation boundary. We showcase the broad applicability of these tags by appending them onto enzymes and demonstrating that the sequestered enzymes remain catalytically active. 

The complex coacervation of proteins with other macromolecules has applications in protein encapsulation and delivery and for determining the function of cellular coacervates. Theoretical or empirical predictions for protein coacervates would enable the design of these coacervates with tunable and predictable structure–function relationships; unfortunately, no such theories exist. To help establish predictive models, the impact of protein-specific parameters on complex coacervation were probed in this study. The complex coacervation of sequence-specific, polypeptide-tagged, GFP variants and a strong synthetic polyelectrolyte was used to evaluate the effects of protein charge patterning on phase behavior. Phase portraits for the protein coacervates demonstrated that charge patterning dictates the protein's binodal phase boundary. Protein concentrations over 100 mg mL −1 were achieved in the coacervate phase, with concentrations dependent on the tag polypeptide sequence covalently attached to the globular protein domain. In addition to shifting the binodal phase boundary, polypeptide charge patterning provided entropic advantages over isotropically patterned proteins. Together, these results show that modest changes of only a few amino acids in the tag polypeptide sequence alter the coacervation thermodynamics and can be used to tune the phase behavior of polypeptides or proteins of interest. 

Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts.