Glucose regulates transcription in yeast through a network of signaling pathways

There is a Corrigendum associated with this document.

Shadia Zaman^1,a, Soyeon I Lippman¹, Lisa Schneper^1,b, Noam Slonim^1,c & James R Broach¹

^aPresent address: NIDDK, National Institutes of Health, Building 10, Room 9C-103, Bethesda, MD 20892, USA

^bPresent address: Department of Molecular Microbiology and Infectious Diseases, College of Medicine, Florida International University, Miami, FL 33199, USA

^cPresent address: IBM Haifa Research Labs, Haifa 31905, Israel

Synopsis

The budding yeast Saccharomyces cerevisiae, similar to other unicellular microorganisms, has evolved to make optimum use of accessible nutrients and to adapt to nutritional deficiencies in a manner that maximizes survival. These behaviors require that yeast cells assess the amount and nature of available nutrients and modify their transcriptional, metabolic and developmental programs in response to that assessment. Saccharomyces uses glucose in preference to other fermentable sugars or oxidizable carbon compounds as a source for its energetic and anabolic needs. Accordingly, Saccharomyces has elaborated a complex, interlocking network of signaling pathways to assess the level of available glucose and to adjust its growth program in response to that assessment (Figure 8). Moreover, Saccharomyces adapts its growth rate, as well as the expression levels of a collection of growth-rate specific genes, in proportion to glucose availability over a wide range of limiting glucose concentrations. In this report, we describe the results of a systems approach that allow us to precisely define the nature of the complex signaling network Saccharomyces uses to assess glucose availability. In addition, we show that Saccharomyces establishes its growth-setting transcriptional program on the basis of its perception of available glucose rather than on its use of that resource.

Figure 8

The glucose signaling network. Diagram of the regulatory wiring connecting the addition of glucose to the transcriptional responses of the cell. Dotted line indicates a limited or indirect connection. See text for details.

Full figure and legend (109K)Figures & Tables index

Several signaling pathways have previously been associated with the glucose perception and response in yeast, although the relative contribution of each and the extent of overlap among them have not been resolved. To define the contributions of these pathways, we pursued a systems-level epistasis analysis. Namely, we examined how much of the glucose response could be recapitulated by activating each of the pathways independently or in combination and, reciprocally, we asked how much of the glucose response was retained in the absence of one or more of the signaling pathways. These results were facilitated by the availability in yeast of genetic tools that allowed de novo activation or elimination of specific signaling pathways. We activated individual pathways by placing a key upstream component of the pathway under control of an inducible promoter that we could turn on with a gratuitous inducer. In many cases, we could instantaneously inactivate a pathway by inhibiting a key kinase intermediate by replacing the wild-type kinase with one engineered to be uniquely sensitive to an AMP analog and then adding the analog to the strain concurrently with glucose addition. The advantage of using these analog-sensitive kinases was that, although the kinase is completely inhibited after addition of the analog, the cells behave completely similar to wild type prior to the addition of the analog. As a consequence, we were not confounded by secondary effects attendant on loss of the kinase activity, as would be the case of using a strain simply deleted for the kinase.

The pathways previously implicated in glucose signaling in yeast are homologous to signaling pathways that play various role in glucose sensing and response in higher eukaryotes: (1) a Ras-activated cAMP-dependent protein kinase (PKA), (2) a TORC1-regulated kinase, Sch9, homologous to mammalian PKB, (3) a heterotrimeric G protein, Gpa2, coupled to a heptahelical receptor, Gpr1, reported to be activated by glucose, (4) a glucose-inhibited kinase, Snf1, homologous to mammalian AMP-activated PK, (5) a transcriptional repressor, Rgt2, regulated by integral plasma membrane glucose sensors and (6) various transcription factors, Hap1–4, responsive to heme levels in the cell. To capture the output of glucose-induced signaling, we measured the global transcriptional response of cells to glucose addition, in which the expression levels of more than 40% of all genes change significantly, and compared that with the global transcriptional response upon activation of individual pathways in the absence of glucose or inactivation of individual pathways concurrently with the addition of glucose. The results of one such experiment are shown in Figure 2D, in which the effect of glucose addition to wild-type cells is compared with glucose addition to cells simultaneously with inactivation of Sch9 and PKA. The results indicate that most of the glucose response is eliminated in the absence of signaling through Sch9 and PKA, except for a residual repressive signal that is mediated predominated by the AMP-activated kinase, Snf1, and a residual inductive signal, mediated predominated by the plasma membrane glucose sensors.

Figure 2

Sch9 plays a minor role in glucose signaling. Microarray expression data presented as in Figure 1. (A) Expression changes of all genes in a P_GAL1-SCH9 strain (Y3506) pregrown on SC+3% glycerol, 40 min after the addition of 2% galactose relative to that at 0 min (y-axis), versus a P_GAL10-RAS2^G19V strain (Y2866) pregrown on SC+3% glycerol, 40 min after galactose addition relative to 0 min (x-axis). Pink dots: cytoplasmic ribosomal protein genes; cyan dots: ribosomal biogenesis genes. Black line is the linear regression for the entire set of genes (slope=0.57) and the pink line passes through the origin and the centroid of ribosomal protein genes (slope=3.14). (B) Same as in (A) except at 60 min post-induction for both strains. (C) Both x- and y-axes show expression changes in sch9^as (strain Y3561) grown on SC+3% glycerol 20 min following the addition of 2% glucose relative to 0 min. For the experiment in the y-axis, 100 nM 1NM-PP1 was added concurrently with glucose. Linear regression line (not shown) has a slope of 1.03 with an R² value of 0.97. (D) Both x- and y-axes show expression changes in tpk1^astpk2^astpk3^assch9^as (strain Y3508) grown on SC+3% glycerol 20 min following the addition of 2% glucose relative to 0 min. For the experiment in the vertical axis, 100 nM 1NM-PP1 was added concurrently with glucose. Green dots: genes whose expression is repressed more than 2 by inactivation of Snf1; orange dots: genes induced more than 2 by activation of Rgt2 (Figure 5).

Figure 1

PKA mediates the primary transcriptional response of cells to glucose. Scatter plots of microarray data for ca. 5600 yeast genes, obtained from two different strains or conditions. Each point represents the log(2) change in levels of the mRNA for a single gene for one strain under one condition in the horizontal dimension and the log(2) change in mRNA levels for that gene in a different strain or condition in the vertical dimension. (A) Expression changes of all genes in a P_GAL10-RAS2^G19V strain (Y2866) pregrown on SC+3% glycerol, 60 min after the addition of 2% galactose relative to that at 0 min (vertical axis), versus a RAS2 strain (Y2864) pregrown on SC+3% glycerol, 20 min after glucose addition relative to 0 min (horizontal axis). (B) Both x- and y-axes show expression changes in P_GAL10-RAS2^G19Vtpk1^astpk2^astpk3^as (strain Y3621) pregrown on SC+3% glycerol, 60 min following the addition of galactose relative to 0 min. For the experiment in the vertical axis, 100 nM 1NM-PP1 was added concurrently with galactose. (C) Both x- and y-axes show expression changes in tpk1^astpk2^astpk3^as (strain Y3561) grown on SC+3% glycerol 20 min following the addition of 2% glucose relative to 0 min. For the experiment in the vertical axis, 100 nM 1NM-PP1 was added concurrently with glucose. Solid black line shows the linear regression (y=0.26x), with the dotted red lines the two-fold limits from the regression line. (D) P_GAL10-RAS2^S24N (strain Y3168), pregrown on SC-glycerol and then preinduced with 2% galactose, 60 min after glucose addition relative to 0 min (vertical axis), versus RAS2 (strain Y2864) under the same conditions (horizontal axis). In all plots, genes whose expression is repressed more than two-fold by inactivation of Snf1 (see Figure 4) are shown in green, genes reported to be regulated by the Hap2/3/4/5 complex are shown in pink and those repressed more than two-fold by 125 M glucose are shown in red.

Figure 4

Snf1 controls a small set of glucose-regulated genes. (A) Strains Y2864 (SNF1) and Y3504 (snf1^as) were grown to a density of A₆₀₀=0.25 in SC+3% glycerol, at which point glucose was added to 2% or mMe-PP1 was added to the indicated concentration (M). The northern blot of RNA samples from cells harvested 1 h after drug treatment, probed for FBP1 and ACT1 is shown. (B) Microarray data presented as in Figure 1 for strain Y3504 (snf1^as) pregrown in SC+3% glycerol 20 min after the addition of 0.4 M mMe-PP1 relative to 0 min (y-axis) or 20 min after the addition of glucose to 2% relative to 0 min (x-axis).

Full figure and legend (250K)Figures & Tables index

Full figure and legend (383K)Figures & Tables index

Figure 5

The Rgt network regulates a small number of glucose-induced genes. (A) Microarray data presented as in Figure 1 for a P_GAL10-RGT2-1 strain pregrown in SC+3% glycerol 60 min after galactose addition relative to 0 min (y-axis) versus a RGT2 strain 20 min after glucose addition relative to 0 min. Genes that showed essentially normal induction by glucose in a tpk1^astpk2^astpk3^assch9^as strain in the presence of 1NM-PP1 (Figure 2) are shown in pink. (B) Expression changes (log(2)) obtained from microarray experiments of the indicated HXT genes as well as STD1 and MTH1 as a function of concentration of glucose 20 min after its addition to wild-type strain Y2864 grown to mid log in SC+3% glycerol.

Full figure and legend (168K)Figures & Tables index

Full figure and legend (270K)Figures & Tables index

Figure 8 summarizes the glucose network that emerged from our studies. Most of the glucose signal proceeds through PKA. Although activation of Sch9, a TORC1-regulated kinase, can recapitulate glucose signaling, Sch9 transmits only a small portion of the glucose signal. Rather, the overlap in response of Sch9 and PKA reflects a common effect of the glucose-induced nutritional response and the TORC1-mediated nitrogen source-induced nutritional response. The Snf1 and Rgt2 pathways regulate a small number of functionally specialized genes, involved in alternate carbon source utilization and hexose transport, respectively. Finally, the heme-regulated transcription factors provide a unique branch that regulates oxidative phosphorylation.

Several surprises emerged from these studies. First, although the apparent glucose receptor, Gpr1, participates in glucose-regulated developmental programs, such as yeast–pseudohyphal transitions, it does not contribute at all to the acute transcriptional response of cells to glucose. Second, Sch9 regulates not only core growth and stress genes in response to nitrogen source, it also directly suppresses signaling through the Gpr1 pathway. This previously unrecognized cross-talk may contribute to the integration of multiple signaling pathways underlying the cell's decision to differentiate into pseudohyphae. Finally, we found that the cell establishes a highly stereotypic growth-promoting transcriptional program—enhancing mass accumulating potential and suppressing stress responses—not on the basis of the ability to use available nutrients but solely on its perception of availability of those nutrients. As a consequence, fooling the cell into thinking such nutrients are available creates a lethal condition as the cell's metabolic reprogramming does not match the nutrients actually available. This observation suggests a novel avenue of therapeutic control not only of microorganisms but also of cancer cells, which have clearly been reprogrammed for nutrient-dependent rapid metabolism.

MORE ARTICLES LIKE THIS

These links to content published by NPG are automatically generated.