Prospective identification of extracellular triacylglycerol hydrolase with conserved amino acids in Amycolatopsis tolypomycina's high G+C genomic dataset

Abstract

Extracellular triacylglycerol hydrolases (ETH) play a critical role for microorganisms, acting as essential tools for lipid breakdown and survival in challenging environments. The pursuit of more effective ETH genes and enzymes through evolution holds significant potential for enhancing living conditions. This study employs a proteogenomic approach to identify high G+C ETH in a notable Gram-positive bacterium, Amycolatopsis tolypomycina. Utilizing knowledge from genome and machine learning algorithms, prospective ETH genes/enzymes were identified. Notably, the ETH structural conserved accessibility to solvent clearly indicated the specific sixteen residues (GLY50, PRO93, GLY141, ASP148, GLY151, ASP172, ALA176, GLY195, TYR196, SER197, GLN198, GLY199, GLY200, GLY225, PRO327, ASP336) with no frequency. By pinpointing key residues and understanding their role, this study sets the stage for enhancing ETH performance through computational proteogenomic and contributes to the broader field of enzyme engineering, facilitating the development of more efficient and versatile ETH enzymes tailored to specific industrial or environmental contexts.