GAL Regulon in the Yeast S. cerevisiae is Highly Evolvable via Acquisition in the Coding Regions of the Regulatory Elements of the Network.

Rajeshkannan Rajeshkannan,Supreet Saini,Anjali Mahilkar

doi:10.3389/fmolb.2022.801011

Rajeshkannan Rajeshkannan, Supreet Saini + Show 1 more

Open Access

https://doi.org/10.3389/fmolb.2022.801011

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Abstract

GAL network in the yeast S. cerevisiae is one of the most well-characterized regulatory network. Expression of GAL genes is contingent on exposure to galactose, and an appropriate combination of the alleles of the regulatory genes GAL3, GAL1, GAL80, and GAL4. The presence of multiple regulators in the GAL network makes it unique, as compared to the many sugar utilization networks studied in bacteria. For example, utilization of lactose is controlled by a single regulator LacI, in E. coli’s lac operon. Moreover, recent work has demonstrated that multiple alleles of these regulatory proteins are present in yeast isolated from ecological niches. In this work, we develop a mathematical model, and demonstrate via deterministic and stochastic runs of the model, that behavior/gene expression patterns of the cells (at a population level, and at a single-cell resolution) can be modulated by altering the binding affinities between the regulatory proteins. This adaptability is likely the key to explaining the multiple GAL regulatory alleles discovered in ecological isolates in recent years.

Highlights

We use the model to ask the following question: how does changing the allelic combinations make to the dynamics of gene expression of the GAL network? Are there specific regulatory elements in the GAL network which control the system’s sensitivity, evolvability than others? We focus on the Gal4p-Gal80p and Gal3*-Gal80p interaction
The ancestral wild type; second, an epistatically-altered strain in which the Gal3*-Gal80p interaction is weakened by a factor of four, and the Gal80p-Gal4p interaction is weakened by a factor of five (Das Adhikari et al, 2014)
The lag phase is the longest when cells are brought from repressing conditions, medium when brought from non-inducing non-repressing (NINR) conditions, and shortest when brought from inducing conditions

Summary

Introduction

Depending on the precise environmental niches, acquisition of a mutation could alter gene expression dynamics more suited for survival and growth. The changes in the network dynamics could be facilitated by two types of mutations. Mutations which change processes like transcription and translation, and shape regulatory networks (Wray, 2007; Kim and Przytycka, 2012; Hill et al, 2021). These mutations change the timing and levels of transcription and translation. Mutations could change protein activity, and as a result the affinity of a protein with DNA or another protein; resulting in downstream changes in gene expression (Golding and Dean, 1998). While several examples of the first kind are known, relatively fewer examples of changes in expression patterns by protein modifications are known (Lewontin, 2002; Rodriguez-Trelles et al, 2003)

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