Determination of the Mating Efficiency of Haploids in <em>Saccharomyces cerevisiae</em>

Saccharomyces cerevisiae is a widely used model organism in genetics, evolution, and molecular biology. In recent years, it has also become a popular ...

Indian Institute of Technology Bombay

University of Michigan, Ann Arbor

Environmental cues in an ecological niche are often temporal in nature. For instance, in temperate climates, temperature is higher in daytime compared to during night. In response to these temporal cues, bacteria have been known to exhibit anticipatory regulation, whereby triggering response to a yet to appear cue. Such an anticipatory response in known to enhance Darwinian fitness, and hence, is likely an important feature of regulatory networks in microorganisms. However, the conditions under which an anticipatory response evolves as an adaptive response are not known. In this work, we develop a quantitative model to study response of a population to two temporal environmental cues, and predict variables which are likely important for evolution of anticipatory regulatory response. We follow this with experimental evolution of  in alternating environments of rhamnose and paraquat for ∼850 generations. We demonstrate that growth in this cyclical environment leads to evolution of anticipatory regulation. As a result, pre-exposure to rhamnose leads to a greater fitness in paraquat environment. Genome sequencing reveals that this anticipatory regulation is encoded  mutations in global regulators. Overall, our study contributes to understanding of how environment shapes the topology of regulatory networks in an organism.

Experimental Evolution of Anticipatory Regulation in .

GAL network in the yeast  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 '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.

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

Mutations provide the raw material for natural selection to act. Therefore, understanding the variety and relative frequency of different type of mutations is critical to understanding the nature of genetic diversity in a population. Mutation accumulation (MA) experiments have been used in this context to estimate parameters defining mutation rates, distribution of fitness effects (DFE), and spectrum of mutations. MA experiments can be performed with different effective population sizes. In MA experiments with bacteria, a single founder is grown to a size of a colony (~ 10<sup>8</sup>). It is assumed that natural selection plays a minimal role in dictating the dynamics of colony growth. In this work, we simulate colony growth via a mathematical model, and use our model to mimic an MA experiment. We demonstrate that selection ensures that, in an MA experiment, fraction of all mutations that are beneficial is over-represented by a factor of almost two, and that the distribution of fitness effects of beneficial and deleterious mutations are inaccurately captured in an MA experiment. Given this, the estimate of mutation rates from MA experiments is non-trivial. We then perform an MA experiment with 160 lines of E. coli, and show that due to the effect of selection in a growing colony, the size and sector of a colony from which the experiment is propagated impacts the results. Overall, we demonstrate that the results of MA experiments need to be revisited taking into account the action of selection in a growing colony.

Selection in a growing colony biases results of mutation accumulation experiments.

Understanding the basis of biological diversity remains a central problem in evolutionary biology. Using microbial systems, adaptive diversification has been studied in (a) spatially heterogeneous environments, (b) temporally segregated resources, and (c) resource specialization in a homogeneous environment. However, it is not well understood how adaptive diversification can take place in a homogeneous environment containing a single resource. Starting from an isogenic population of yeast Saccharomyces cerevisiae, we report rapid adaptive diversification, when propagated in an environment containing melibiose as the carbon source. The diversification is driven due to a public good enzyme α-galactosidase, which hydrolyzes melibiose into glucose and galactose. The diversification is driven by mutations at a single locus, in the GAL3 gene in the S. cerevisiae GAL/MEL regulon. We show that metabolic co-operation involving public resources could be an important mode of generating biological diversity. Our study demonstrates sympatric diversification of yeast starting from an isogenic population and provides detailed mechanistic insights into the factors and conditions responsible for generating and maintaining the population diversity.

Anjali Mahilkar

Department of Chemical Engineering

Indian Institute of Technology Bombay

Determination of the Mating Efficiency of Haploids in Saccharomyces cerevisiae

Anjali Mahilkar

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Chemical Engineering

Indian Institute of Technology Bombay

Determination of the Mating Efficiency of Haploids in Saccharomyces cerevisiae

Department of Chemical Engineering