High-Throughput Imaging of Arrays of Fluorescently Tagged Yeast Mutant Strains.

We describe a protocol for live-cell high-throughput (HTP) screening of yeast mutant strains carrying fluorescent protein markers for subcellular compartments of choice using automated confocal microscopy. This procedure, which combines HTP genetics and microscopy, results in the acquisition of thousands of images that can be analyzed in a systematic and quantitative way to identify morphology defects in the tagged subcellular compartments. This HTP protocol is readily adapted for screening any combination of markers and can be expanded to different growth conditions or higher order mutant genetic backgrounds.

Machine learning and computer vision approaches for phenotypic profiling.

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach.

Too much of a good thing: the unique and repeated paths toward copper adaptation.

Copper is a micronutrient essential for growth due to its role as a cofactor in enzymes involved in respiration, defense against oxidative damage, and iron uptake. Yet too much of a good thing can be lethal, and yeast cells typically do not have tolerance to copper levels much beyond the concentration in their ancestral environment. Here, we report a short-term evolutionary study of Saccharomyces cerevisiae exposed to levels of copper sulfate that are inhibitory to the initial strain.

Parallel genetic changes and nonparallel gene-environment interactions characterize the evolution of drug resistance in yeast.

Beneficial mutations are required for adaptation to novel environments, yet the range of mutational pathways that are available to a population has been poorly characterized, particularly in eukaryotes. We assessed the genetic changes of the first mutations acquired during adaptation to a novel environment (exposure to the fungicide, nystatin) in 35 haploid lines of Saccharomyces cerevisiae. Through whole-genome resequencing we found that the genomic scope for adaptation was narrow; all adapted lines acquired a mutation in one of four late-acting genes in the ergosterol biosynthesis pathway, with very few other mutations found.