CAREER: Topological effect on protein phase separation

Non‑Technical Summary Recent advances in biotechnology reveal that some proteins can assemble dynamic clusters inside cells and in engineered systems. These protein-based assemblies hold great promises for applications in biotechnology and bioengineering. Until now, most research efforts to control the behavior of the protein assembly have focused on protein chemistry, such as changing the amino acid sequences that make up the protein. However, emerging research shows that an overlooked property, how a protein is connected (for example, forming a ring or a pom-pom-like structure rather than a simple chain), can dramatically alter how these materials behave and function. This CAREER project explores protein connectivity as a powerful and previously untapped strategy for designing biomaterials with programmable properties. By engineering proteins with ring‑shaped or branched architectures, the project aims to determine how protein connectivity governs material behaviors. The work challenges long‑standing assumptions and contributes to an understudied area in current biotechnology and biomaterials research. The outcomes from the project advance fundamental understanding of how biomaterials self‑organize and enable new approaches for creating adaptable and functional biomaterials. An integrated research and education program train students in advanced biotechnology, materials sciences, and AI‑based data-driven modeling. Outreach efforts include hands-on demonstrations and community engagement activities with K-12 students to increase public understanding of biotechnology and materials science. Technical Summary Biomolecular condensates formed by protein phase separation represent a versatile class of biomaterials with dynamic, tunable properties. Traditional approaches to manipulate biomolecular condensates and control their phase separation behaviors have focused on modifying protein sequence; however, efforts on optimizing protein sequences have yielded diminishing returns, motivating the need for alternative and orthogonal methods to modulate biomaterial properties. Emerging preliminary data indicates that protein topology, specifically non-linear architectures such as circular or branched proteins, can exert unexpected effects on protein phase separation behavior. These observations are contrary to prevailing polymer-based theoretical predictions and the mechanistic understanding advances biotechnology methods and platform for broad biomaterial applications. This CAREER project investigates protein topology as a critical and previously understudied determinant of biomolecular condensate material properties. The central hypothesis is that non-linear protein topologies represent a significant parameter in biomolecular condensate dynamics that can give rise to unique gel-like behaviors and novel material states. Objective 1 examines how circularized protein architectures influence phase separation, condensate dynamics, and material properties relative to linear proteins. Objective 2 extends this investigation to branched protein topologies. Objective 3 identifies molecular mechanisms governing the emergent properties of non-linear biomolecular condensates through integrated experimental characterization and computational modeling. This work generates systematic experimental data set on topological effects in protein phase separation and refines theoretical frameworks to incorporate both sequence and topology effects. Beyond advancing fundamental understanding, the project promotes biotechnology with a clear relevance to biomaterials design. This work develops and optimizes generalizable strategies for producing circular and branched proteins to enable broader application of topology-driven material design. The educational component integrates research to train students in biotechnology, materials science, and AI-based data-driven modeling. Through engaging interactions with K-12 students, the outreach activities incorporate NSF Award ID: 2544133 | Program: 01003031DB NSF RESEARCH & RELATED ACTIVIT,01002930DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Juan Guan | Institution: University of Texas at Austin, AUSTIN, TX | Award Amount: $422,993 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2544133 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2544133.html