2024 AIChE Annual Meeting

(4x) Establishing Extremophiles As High-Throughput Screening Platform for Protein Engineering

Authors

Sandra Oloketuyi, Los Alamos National Laboratory
Brian Harriman, Los Alamos National Laboratory
Raul Gonzalez-Esquer, Los Alamos National Laboratory
Sang-Min Shin, Los Alamos National Laboratory
Ramesh Jha, Los Alamos National Laboratory
Abstract: Bioprocesses driven by bioconversion can play a major role in our transition to a sustainable future. Enzymes can perform bioconversions with utmost accuracy and finesse, especially when the requirements of the catalytic process are compatible with the enzyme’s optimum reaction condition. However, the widespread use of enzymes is not efficiently met due to the non-optimal catalytic properties and a knowledge gap for biotechnologically important enzymes, which are commonly mesophilic in nature and often not suitable for industrial bioprocesses where prolonged activities would be required under harsh conditions arising from media compositions or high temperature requirements. This presentation will discuss our efforts in developing a high-throughput screening platform for thermostable proteins in hyperthermophilic bacteria Thermotoga maritima. The key bottlenecks in Design-Build-Test-Learn cycle were addressed via establishing T. maritima as a chassis with high transformation efficiency and heterologous protein expression capability. Overall, we expect our efforts will lead to an implemented technology, which will substantially simplify extremozyme discovery and engineering.

Research Interests

Dr. Jingyao Li is currently a postdoctoral research associate at Los Alamos National Laboratory. He completed his Ph.D. in Chemical Engineering from Washington University in St. Louis in January 2024. His Ph.D. research focuses on developing high-performance protein-based biomaterials. Dr. Li is particularly interested in the de novo design of functional proteins and enzymes using computational and high-throughput screening methods to facilitate industrial bioproduction processes.