Biomarcomolecular phase separation and assembly in elastic environments

Non-technical description Cartilage can cushion joints for decades, squid skin can change how it reflects light, and cells can build tiny liquid-like droplets that organize chemistry without using membranes. These materials all rely on a difficult trick: molecules must decide where to gather, how large to grow, and how to align inside crowded, elastic surroundings. Learning how nature achieves this kind of organization will create new opportunities in biotechnology, including better tissue scaffolds, responsive drug-delivery materials, and biosensors. This project asks how the material properties of soft, water-filled networks guide biological self-assembly. The team will build simplified versions of these systems and adjust the things nature tunes: how stiff the surrounding material is, the salt concentration, and how the network is structured at the smallest scales. By changing these conditions, the researchers can learn what makes proteins assemble and order and switch that organization on and off using simple triggers. The resulting fundamental understanding will help create 3D-printable biomaterials that organize themselves from within yet still respond to their surroundings. To speed translation from lab to application, the project partners with regional manufacturing and innovation organizations and trains undergraduate and graduate students, strengthening the biotechnology workforce in Northeast Ohio. Technical description Advancing biotechnology requires predictive control over how biomacromolecules assemble within crowded, elastic matrices. This project tests the hypothesis that local elasticity and anisotropy regulate phase behavior and order. Resolving these mechanisms will create new biotechnology opportunities in responsive delivery systems, biosensors, engineered extracellular-matrix scaffolds, and self-organizing biomaterials. The research has three objectives. Objective 1 will map the phase behavior, kinetics, and network permeation of model biomacromolecular phase separating systems in polyacrylamide gels with controlled modulus, ionic strength, and concentration. These results will be used to develop a thermodynamic model that explains how crowding, osmotic stress, and elastic deformation combine to control phase behavior. Objective 2 will compare flexible polyacrylamide networks and fibrillar thermoresponsive methylcellulose networks to determine how rigidity and anisotropy influence organization. Objective 3 will test network heterogeneity by comparing order in perfect networks with heterogeneous ones. Building on preliminary results showing that matrix elasticity controls phase behavior and size scales, this work will establish fundamental mechanisms by which elasticity regulates biomacromolecular phase behavior and assembly. The broader impacts connect self-organizing soft materials to future biotechnology applications, including artificial tissues, wearable sensors, 3D-printed functional materials, and enzymatically active systems. Students will gain hands-on training in biomaterials research, imaging, prototyping, and translation through regional partnerships with local innovation centers, manufacturers, and soft-matter groups, strengthening the biotechnology and advanced-manufacturing workforce in Northeast Ohio. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2610176 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Svetlana Morozova | Institution: Case Western Reserve University, CLEVELAND, OH | Award Amount: $427,913 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2610176 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2610176.html