Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Coarse-Grained Modeling Elucidates Differential Metabolism of Saccharomyces cerevisiae under Varied Nutrient Limitations

Microorganisms such as Saccharomyces cerevisiae have a native ability to adapt their metabolism to varying nutrient conditions. Understanding their responses to nutrient limitations is critical for decoding cellular physiology and designing strategies for metabolic engineering. While the influence of carbon availability on yeast metabolism has been extensively studied, the role of nitrogen availability remains relatively underexplored. In this study, we utilized a coarse-grained kinetic model to systematically analyze and compare the effects of carbon and nitrogen limitations on yeast metabolism. Our model successfully revealed the differential metabolic characteristics of S. cerevisiae under carbon- and nitrogen-limited chemostat conditions. It also highlighted the significance of protein activity regulation at varying carbon-to-nitrogen ratios, and elucidated distinct strategies employed to maintain ATP homeostasis. This study provides a computational tool for investigating yeast physiology under nutrient limitations and offers quantitative and mechanistic insights into yeast metabolism.

The Role of Phenotypic Plasticity and Within-Environment Trait Variability in the Assembly of the Nectar Microbiome and Plant-Microbe-Animal Interactions

The study of the rules that govern the relationship between phenotypic plasticity, genetic structure, and ecological success has traditionally focused on animals, plants, and a few model microbial species, whereas non-model microorganisms have received much less attention in this regard. The floral nectar of angiosperms is an ephemeral, island-like habitat for different highly adapted yeasts and bacteria. The growth of microorganisms in floral nectar depends on their ability to efficiently use the available nutrients and tolerate challenging physicochemical conditions, including high osmotic pressures, unbalanced carbon-to-nitrogen ratios, and the presence of diverse defensive compounds of plant origin. The production of alternative phenotypic states in response to environmental cues (i.e., phenotypic plasticity) or independently from these (within-environment trait variability) might be particularly relevant in floral nectar, in which rapid growth is needed for population persistence and to improve the chance of animal-mediated dispersal. In this article, we use the nectar microbiome as an example to encourage further research on the causes and ecological consequences of phenotypic plasticity and within-environment trait variability of microbes. We review previous work on the mechanisms and potential ecological significance of the phenotypic plasticity and within-environment trait variability displayed by nectar yeasts and bacteria. Additionally, we provide an overview of some topics that require further attention, including potential trade-offs between different traits that are relevant for adaptation to dynamic nectar environments and the direct and indirect effects of phenotypic variability on the fitness of plants, flower-visiting animals, and other nectar microbes. We conclude that further research on the causes and ecological consequences of phenotypic plasticity and within-environment trait variability of microbes is essential to get a better understanding of community assembly and the establishment of ecological interactions in floral nectar and other similar highly dynamic and strongly selective microbial habitats.

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as proteins, for growth optimization. Recent experiments have begun to reveal molecular components unpinning the partition; however, quantitatively, it remains unclear how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here, we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that the cellular ability of resource partition lies in an ultrasensitive, negative feedback-controlling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism that mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations and is also efficient for biomass production over time. This work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.