Drug-dependent growth curve reshaping reveals mechanisms of antifungal resistance in Saccharomyces cerevisiae.

Microbial drug resistance is an emerging global challenge. Current drug resistance assays tend to be simplistic, ignoring complexities of resistance manifestations and mechanisms, such as multicellularity. Here, we characterize multicellular and molecular sources of drug resistance upon deleting the AMN1 gene responsible for clumping multicellularity in a budding yeast strain, causing it to become unicellular. Computational analysis of growth curve changes upon drug treatment indicates that the unicellular strain is more sensitive to four common antifungals. Quantitative models uncover entwined multicellular and molecular processes underlying these differences in sensitivity and suggest AMN1 as an antifungal target in clumping pathogenic yeasts. Similar experimental and mathematical modeling pipelines could reveal multicellular and molecular drug resistance mechanisms, leading to more effective treatments against various microbial infections and possibly even cancers.

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells.

Reliable gene expression control in mammalian cells requires tools with high fold change, low noise, and determined input-to-output transfer functions, regardless of the method used. Toward this goal, optogenetic gene expression systems have gained much attention over the past decade for spatiotemporal control of protein levels in mammalian cells. However, most existing circuits controlling light-induced gene expression vary in architecture, are expressed from plasmids, and utilize variable optogenetic equipment, creating a need to explore characterization and standardization of optogenetic components in stable cell lines. Here, the study provides an experimental pipeline of reliable gene circuit construction, integration, and characterization for controlling light-inducible gene expression in mammalian cells, using a negative feedback optogenetic circuit as a case example. The protocols also illustrate how standardizing optogenetic equipment and light regimes can reliably reveal gene circuit features such as gene expression noise and protein expression magnitude. Lastly, this paper may be of use for laboratories unfamiliar with optogenetics who wish to adopt such technology. The pipeline described here should apply for other optogenetic circuits in mammalian cells, allowing for more reliable, detailed characterization and control of gene expression at the transcriptional, proteomic, and ultimately phenotypic level in mammalian cells.