Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

Background: Scheffersomyces stipitis is an important yeast species in the field of biorenewables due to its desired capacity for xylose utilization. It has been recognized that redox balance plays a critical role in S. stipitis due to the different cofactor preferences in xylose assimilation pathway.

Comprehensive evaluation of two genome-scale metabolic network models for Scheffersomyces stipitis.

Genome-scale metabolic network models represent the link between the genotype and phenotype of the organism, which are usually reconstructed based on the genome sequence annotation and relevant biochemical and physiological information. These models provide a holistic view of the organism's metabolism, and constraint-based metabolic flux analysis methods have been used extensively to study genome-scale cellular metabolic networks. It is clear that the quality of the metabolic network model determines the outcome of the application.

An improved dynamic method to measure kL a in bioreactors.

An accurate measurement or estimation of the volumetric mass transfer coefficient kL a is crucial for the design, operation, and scale up of bioreactors. Among different physical and chemical methods, the classical dynamic method is the most widely applied method to simultaneously estimate both kL a and cell's oxygen utilization rate. Despite several important follow-up articles to improve the original dynamic method, some limitations exist that make the classical dynamic method less effective under certain conditions.