From static definitions to dynamic landscapes: physiological states in yeast

Physiological states have traditionally been defined as discrete and static categories derived from snapshot measurements. This approach ignores the dynamic and context-dependent nature of cellular behavior. We propose a shift from static definitions to a dynamic landscape framework to describe the physiological states in yeast. Focusing on adaptation, viability, and vitality,-three states of industrial relevance,-we integrated transcriptomic analyses in Saccharomyces cerevisiae and Kluyveromyces marxianus which represent gradual transitions rather than isolated entities. Returning to Waddington's epigenetic landscape metaphor, we conceptualized physiological states as attractors in a high-dimensional space shaped by regulatory, metabolic, and environmental factors, where cell dynamics follow trajectories between attraction basins. This perspective provides a theoretical framework for integrating multi-omics data and advancing the prediction and control of cellular behavior in biotechnological systems.