Salvado, B. | Search bioRxiv

bioRxiv2020

What influences selection of native phosphorelay architectures?

Phosphorelays are signal transduction circuits that combine four different phosphorylatable protein domains for sensing environmental changes and use that information to adjust cellular metabolism to the new conditions in the milieu. Five alternative circuit architectures account for more than 99% of all phosphorelay operons annotated in over 9000 fully sequenced genomes, with one of those architectures accounting for more than 72% of all cases. Here we asked if there are biological design principles that explain the selection of preferred phosphorelay architectures in nature and what might those principles be. We created several types of data-driven mathematical models for the alternative phosphorelay architectures, exploring the dynamic behavior of the circuits in concentration and parameter space, both analytically and through over 108 numerical simulations. We compared the behavior of architectures with respect to signal amplification, speed and robustness of the response, noise in the response, and transmission of environmental information to the cell. Clustering analysis of massive Monte Carlo simulations suggests that either information transmission or metabolic cost could be important in selecting the architecture of the phosphorelay. A more detailed study using models of kinetically well characterized phosphorelays (Spo0 of Bacillus subtilis and Sln1-Ypd1-Ssk1-Skn7 of Saccharomyces cerevisiae) shows that information transmission is maximized by the natural architecture of the phosphorelay. In view of this we analyze seventeen additional phosphorelays, for which protein abundance is available but kinetic parameters are not. The architectures of 16 of these are also consistent with maximization of information transmission. Our results highlight the complexity of the genotype (architecture, parameter values, and protein abundance) to phenotype (physiological output of the circuit) mapping in phosphorelays. The results also suggest that maximizing information transmission through the circuit is important in the selection of natural circuit genotypes.

systems biology↗

bioRxiv2017

Metabolic Constraints And Quantitative Design Principles In Gene Expression During Adaption Of Yeast To Heat Shock

Microorganisms evolved adaptive responses that enable them to survive stressful challenges in ever changing environments by adjusting metabolism through the modulation of gene expression, protein levels and activity, and flow of metabolites. More frequent challenges allow natural selection ampler opportunities to select from a larger number of phenotypes that are compatible with survival. Understanding the causal relationships between physiological and metabolic requirements that are needed for cellular stress adaptation and gene expression changes that are used by organisms to achieve those requirements may have a significant impact in our ability to interpret and/or guide evolution.\n\nHere, we study those causal relationships during heat shock adaptation in the yeast Saccharomyces cerevisiae. We do so by combining dozens of independent experiments measuring whole genome gene expression changes during stress response with a nonlinear simplified kinetic model of central metabolism.\n\nThis combination is used to create a quantitative, multidimensional, genotype-to-phenotype mapping of the metabolic and physiological requirements that enable cell survival to the feasible changes in gene expression that modulate metabolism to achieve those requirements. Our results clearly show that the feasible changes in gene expression that enable survival to heat shock are specific for this stress. In addition, they suggest that genetic programs for adaptive responses to desiccation/rehydration and to pH shifts might be selected by physiological requirements that are qualitatively similar, but quantitatively different to those for heat shock adaptation. In contrast, adaptive responses to other types of stress do not appear to be constrained by the same qualitative physiological requirements. Our model also explains at the mechanistic level how evolution might find different sets of changes in gene expression that lead to metabolic adaptations that are equivalent in meeting physiological requirements for survival. Finally, our results also suggest that physiological requirements for heat shock adaptation might be similar between unicellular ascomycetes that live in similar environments. Our analysis is likely to be scalable to other adaptive response and might inform efforts in developing biotechnological applications to manipulate cells for medical, biotechnological, or synthetic biology purposes.

systems biology↗