Building a machine-learning model to predict optimal mevalonate pathway gene expression levels for efficient production of a carotenoid in yeast.

Simultaneous modification of the expression levels of many metabolic enzyme genes results in diverse expression ratios of these genes; however, the relationship between gene expression levels and chemical productivity remains unclear. However, clarification of this relationship is expected to improve the productivity of useful chemicals. Supervised machine learning is considered to be an effective means to clarify this relationship.

Recent structural insights into the mechanism of lysozyme hydrolysis.

Lysozyme hydrolyzes the glycosidic bonds between N-acetylmuramic acid and N-acetylglucosamine in peptidoglycans located in the bacterial cell wall. The mechanism of the hydrolysis reaction of lysozyme was first studied more than 50 years ago; however, it has not yet been fully elucidated and various mechanisms are still being investigated. One reaction system that has commonly been proposed is that the lysozyme intermediate undergoes covalent ligand binding during hydrolysis.