Using colony size to measure fitness in Saccharomyces cerevisiae

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast could be driven by a number of factors including niche differences or differential access to resistance mutations between species. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants. We found that the distributions of mutational effects displayed by the two species were similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a de novo duplication of the CUP1 gene in S. paradoxus but not in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger effects in S. paradoxus. Our results show that even when available mutations are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

Quantifying massively parallel microbial growth with spatially mediated interactions

Quantitative understanding of microbial growth is an essential prerequisite for successful control of pathogens as well as various biotechnology applications. Even though the growth of cell populations has been extensively studied, microbial growth remains poorly characterised at the spatial level. Indeed, even isogenic populations growing at different locations on solid growth medium typically show significant location-dependent variability in growth. Here we show that this variability can be attributed to the initial physiological states of the populations, the interplay between populations interacting with their local environment and the diffusion of nutrients and energy sources coupling the environments. We further show how the causes of this variability change throughout the growth of a population. We use a dual approach, first applying machine learning regression models to discover that location dominates growth variability at specific times, and, in parallel, developing explicit population growth models to describe this spatial effect. In particular, treating nutrient and energy source concentration as a latent variable allows us to develop a mechanistic resource consumer model that captures growth variability across the shared environment. As a consequence, we are able to determine intrinsic growth parameters for each local population, removing confounders common to location-dependent variability in growth. Importantly, our explicit low-parametric model for the environment paves the way for massively parallel experimentation with configurable spatial niches for testing specific eco-evolutionary hypotheses.

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus, has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast represents a case of apparent evolutionary constraints favoring greater adaptive capacity in S. cerevisiae. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants isolated from our screen. We found that the distributions of mutational effects displayed by the two species were very similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a single de novo duplication of the CUP1 gene in S. paradoxus but none in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger average effects in S. paradoxus. Our results show that even when the distributions of mutational effects are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

A Matlab-based application for quantification of yeast cell growth on solid media

Quantitative assessment of growth and survival is a suitable technique in studying biochemical, genetic and physiological processes in the cells. The budding yeast Saccharomyces cerevisiae is one of the most widely used eukaryotic model organisms for studying cellular mechanisms and processes in evolutionarily distant species, including humans. Yeast growth can be evaluated on both liquid and solid media by measuring cell suspension turbidity and colony forming units, respectively. Several software tools utilizing different parameters have been proposed to quantify yeast growth on solid media. Here, we developed a Matlab-based application which provides a rapid and robust quantitative yeast growth analysis from spot plating assay. Spot plating assay is a typical procedure to evaluate yeast growth in low-throughput laboratory settings, including growth on different nutrient sources or treatment with specific stressors. The app has a one-step installation process, a self-explanatory interface and shorter analysis steps compared with previous established methods, providing a useful tool for both expert and non-expert yeast researchers.

Experimental evolution of Saccharomyces uvarum at high temperature yields elevation of maximal growth temperature and loss of the mitochondrial genome

An organism's upper thermal tolerance is a major driver of its ecology and is a complex, polygenic trait. Given the wide variance in this critical phenotype across the tree of life, it is quite striking that this trait has not proven very evolutionarily labile in experimental evolution studies of microbes. In stark contrast to recent studies, William Henry Dallinger in the 1880s reported increasing the upper thermal limit of microbes he experimentally evolved by >40°C using a very gradual temperature ramping strategy. Using a selection scheme inspired by Dallinger, we sought to increase the upper thermal limit of Saccharomyces uvarum . This species has a maximum growth temperature of 34-35°C, considerably lower than S. cerevisiae . After 136 passages on solid plates at progressively higher temperatures, we recovered a clone that can grow at 36°C, a gain of ~1.5°C. Additionally, the evolved clone lost its mitochondrial genome and cannot respire. In contrast, an induced rho 0 derivative of the ancestor shows a decrease in thermotolerance. Also, incubation of the ancestor at 34°C for 5 days increased the frequency of petite mutants drastically compared to 22°C, supporting the notion that mutation pressure rather than selection drove loss of mtDNA in the evolved clone. These results demonstrate that S. uvarum 's upper thermal limit can be elevated slightly via experimental evolution and corroborate past observations in S. cerevisiae that high temperature selection schemes can inadvertently lead to production of the potentially undesirable respiratory incompetent phenotype in yeasts.