Lijun Zhou awarded NSF Career Award

Congratulations to AIRFoundry PI, Lijun Zhou, on being awarded a National Science Foundation Faculty Early Career Development Program. Awarded by the Chemical of Life Process program, Zhou’s project is titled, “Engineering and In Vitro Evolution of XNAs as a Platform for Protein Recognition and Aggregation Control.”

Proposal abstract: Researchers from the University of Pennsylvania are developing biotechnology platforms based on synthetic genetic polymers, known as xeno nucleic acids (XNAs). These platforms could be applied to discover functional molecules that recognize and regulate disease-related proteins. Many human diseases, including neurodegenerative disorders, are associated with abnormal protein aggregation, yet existing molecular tools often lack the stability and specificity needed to investigate or control these dynamic biological processes. Unlike natural nucleic acids, many XNAs possess enhanced chemical stability and unique structural properties that may enable new modes of molecular recognition.

The research team will establish in vitro evolution (SELEX) platforms to identify functional XNAs capable of selectively interacting with proteins involved in aggregation. Their discoveries could provide new tools for studying RNA-protein interactions and biomolecular condensates, and advance biotechnology by expanding the applications of synthetic nucleic acids. The project will also integrate research with education by training graduate and undergraduate students, engaging K-12 students through outreach activities, developing publicly accessible educational resources, and providing workshops that broaden participation in nucleic acid chemistry and synthetic biology.

This project will establish two complementary XNA-SELEX platforms for the de novo evolution of functional XNAs. Using the aggregation-prone RNA-binding protein FUS as a model system, the research team will investigate how synthetic nucleic acids influence protein recognition, liquid-liquid phase separation, and protein aggregation through biochemical and biophysical analyses. Comparisons between natural RNA and synthetic XNAs will provide insight into how nucleic acid chemistry influences protein recognition and aggregation behavior. XNA-SELEX workflows will then be developed and optimized to identify functional XNAs capable of selectively recognizing and regulating aggregation-prone proteins. Selected XNAs will be characterized to determine their binding properties, structural features, and mechanisms of action. These studies will establish general principles linking nucleic acid chemistry to protein recognition and aggregation control. The resulting XNA-SELEX platforms are expected to provide broadly applicable methods for discovering synthetic nucleic acids targeting diverse proteins, thereby expanding the molecular toolkit for biotechnology and chemical biology.

Abstract copied from NSF award #2543709.