Computational analysis of GAL pathway pinpoints mechanisms underlying natural variation.

Quantitative traits are measurable phenotypes that show continuous variation over a wide phenotypic range. Enormous effort has recently been put into determining the genetic influences on a variety of quantitative traits with mixed success. We identified a quantitative trait in a tractable model system, the GAL pathway in yeast, which controls the uptake and metabolism of the sugar galactose. GAL pathway activation depends both on galactose concentration and on the concentrations of competing, preferred sugars such as glucose. Natural yeast isolates show substantial variation in the behavior of the pathway. All studied yeast strains exhibit bimodal responses relative to external galactose concentration, i.e. a set of galactose concentrations existed at which both GAL-induced and GAL-repressed subpopulations were observed. However, these concentrations differed in different strains. We built a mechanistic model of the GAL pathway and identified parameters that are plausible candidates for capturing the phenotypic features of a set of strains including standard lab strains, natural variants, and mutants. In silico perturbation of these parameters identified variation in the intracellular galactose sensor, Gal3p, the negative feedback node within the GAL regulatory network, Gal80p, and the hexose transporters, HXT, as the main sources of the bimodal range variation. We were able to switch the phenotype of individual yeast strains in silico by tuning parameters related to these three elements. Determining the basis for these behavioral differences may give insight into how the GAL pathway processes information, and into the evolution of nutrient metabolism preferences in different strains. More generally, our method of identifying the key parameters that explain phenotypic variation in this system should be generally applicable to other quantitative traits.

Computational study on ratio-sensing in yeast galactose utilization pathway.

Metabolic networks undergo gene expression regulation in response to external nutrient signals. In microbes, the synthesis of enzymes that are used to transport and catabolize less preferred carbon sources is repressed in the presence of a preferred carbon source. For most microbes, glucose is a preferred carbon source, and it has long been believed that as long as glucose is present in the environment, the expression of genes related to the metabolism of alternative carbon sources is shut down, due to catabolite repression. However, recent studies have shown that the induction of the galactose (GAL) metabolic network does not solely depend on the exhaustion of glucose. Instead, the GAL genes respond to the external concentration ratio of galactose to glucose, a phenomenon of unknown mechanism that we termed ratio-sensing. Using mathematical modeling, we found that ratio-sensing is a general phenomenon that can arise from competition between two carbon sources for shared transporters, between transcription factors for binding to communal regulatory sequences of the target genes, or a combination of the aforementioned two levels of competition. We analyzed how the parameters describing the competitive interaction influenced ratio-sensing behaviors in each scenario and found that the concatenation of both layers of signal integration could expand the dynamical range of ratio-sensing. Finally, we investigated the influence of circuit topology on ratio-sensing and found that incorporating negative auto-regulation and/or coherent feedforward loop motifs to the basic signal integration unit could tune the sensitivity of the response to the external nutrient signals. Our study not only deepened our understanding of how ratio-sensing is achieved in yeast GAL metabolic regulation, but also elucidated design principles for ratio-sensing signal processing that can be used in other biological settings, such as being introduced into circuit designs for synthetic biology applications.

Low Cell-Matrix Adhesion Reveals Two Subtypes of Human Pluripotent Stem Cells.

We show that a human pluripotent stem cell (hPSC) population cultured on a low-adhesion substrate developed two hPSC subtypes with different colony morphologies: flat and domed. Notably, the dome-like cells showed higher active proliferation capacity and increased several pluripotent genes' expression compared with the flat monolayer cells. We further demonstrated that cell-matrix adhesion mediates the interaction between cell morphology and expression of KLF4 and KLF5 through a serum response factor (SRF)-based regulatory double loop. Our results provide a mechanistic view on the coupling among adhesion, stem cell morphology, and pluripotency, shedding light on the critical role of cell-matrix adhesion in the induction and maintenance of hPSC.