Metabolomics and Network Biology for sensitive monitoring of how growth environment changes affect the physiology of industrial-scale perfusion cultures

Abstract

Metabolomic analysis can indeed enhance the prime variable dataset for the monitoring of perfusion cultures by providing a higher resolution view of the metabolic state. Metabolic profiles can capture physiological state shifts over the course of the perfusion cultures and indicate a metabolic “signature” of the phase transitions, which is not observable from prime variable data. Notably, metabolomics provides orthogonal (to prime variables) evidence that all cultures follow this same metabolic state shift with cell age, independently of bioreactor scale. Additionally, this analysis can increase the information content of process development experiments by helping better understand the impact of changes in bioreactor operating conditions on cell physiology. In this context, metabolic profiling could be integrated into the monitoring of cell physiology in perfusion cultures.