Recently much work has been devoted to understanding the design principles of the genetic regulatory networks used by cells to respond to changes in the extracellular environment. Many of these investigations have combined mathematical modeling with experimental investigations to establish how simple network motifs, such as feed forward or feedback loops, tightly regulate temporal patterns of gene expression. Here we use a similar approach to discover novel functions for a class of negative regulators that inhibit transcription by binding to and repressing transcriptional activators. We focus on transcriptional regulation in the mating response of Saccharomyces cerevisiae (yeast). This system has served as a prototypical signaling network, and many of the discoveries made from studying this pathway have borne direct relevance to signaling in human cells.
Yeast can stably propagate as haploids, existing as one of two mating types, depending on the allele at the mating-type locus (MATa
α). Both MATa
α cells secrete a mating-type-specific pheromone (a
- and α-factor, respectively) that signals their presence to cells of opposite mating type. Much is known about the pathway that receives the extracellular signal and initiates a mating response. Genome-wide analysis has established the genes that are regulated during this process (Roberts et al, 2000
). Typically, these genes contain pheromone responsive elements (PREs) in their promoter regions. The protein Ste12 is the primary transcription activator responsible for initiating the genetic program required for mating. Prior to stimulation with pheromone, Ste12 is held inactive by the negative regulators Dig1 and Dig2 (Cook et al, 1996
; Tedford et al, 1997
; Bardwell et al, 1998
). Stimulation of MATa
cells with α-factor leads to dissociation of Dig1 and Dig2, allowing Ste12 to initiate transcription from promoters containing PREs. Expression from promoters containing PREs is typically transient, with mRNA levels peaking at around 30
min following stimulation with pheromone before returning to near basal levels. This transient response is significantly shorter than upstream MAP kinase activity, which does not peak until around 60
min (Hao et al, 2008
). This difference in time scales suggests a regulatory mechanism at or below the level of the MAP kinase that dampens Ste12 activity. Indeed, it has been demonstrated that Ste12 is degraded in pheromone-dependent manner (Esch et al, 2006
). However, Ste12 is also under the regulation of four PREs, generating a positive feedback loop in the system (Zeitlinger et al, 2003
). Additionally, Ste12 binds to another transcription factor, Tec1. In nutrient-limiting conditions, the Ste12–Tec1 heterodimer is one of the key transcriptional regulators of the genetic program needed for the filamentous response (Madhani and Fink, 1997
). This interaction with Tec1 further complicates the picture of transcriptional regulation by Ste12. The existence of multiple positive and negative control mechanisms makes understanding transcriptional regulation by the pheromone signaling pathway non-intuitive. For example, Chou et al (2008)
recently demonstrated that deletion of the gene encoding the repressor Dig2 led to a decrease rather than an increase in pheromone-induced transcription. Therefore, we sought to combine mathematical modeling with experimental investigations to understand how this system regulates transcription to ensure that the correct genetic program is followed.
Our investigations led to the discovery of two novel functions for the negative regulators Dig1 and Dig2. In addition to inhibiting Ste12, Dig1 and Dig2 protect the transcriptional activator from degradation. This protective binding ensures a large pool of inactive Ste12 is present prior to pheromone stimulation and allows the system to respond rapidly once a signal is received. Additionally, we show that the protective binding naturally generates a transient response to a sustained pheromone exposure with the amount of active Ste12 eventually returning exactly to its prestimulus level (perfect adaptation). We use a reduced version of the model to demonstrate how this adaptive behavior is achieved without the need for additional forms of negative regulation.