A Toolkit for Precise, Multigene Control in Saccharomyces cerevisiae.

Systems that allow researchers to precisely control the expression of genes are fundamental to biological research, biotechnology, and synthetic biology. However, few inducible gene expression systems exist that can enable simultaneous multigene control under common nutritionally favorable conditions in the important model organism and chassis Saccharomyces cerevisiae. Here we repurposed ligand binding domains from mammalian type I nuclear receptors to establish a family of up to five orthogonal synthetic gene expression systems in yeast. Our systems enable tight, independent, multigene control through addition of inert hormones and are capable of driving robust and rapid gene expression outputs, in some cases achieving up to 600-fold induction. As a proof of principle, we placed expression of four enzymes from the violacein biosynthetic pathway under independent expression control to selectively route pathway flux by addition of specific inducer combinations. Our results establish a modular, versatile, and potentially expandable toolkit for multidimensional control of gene expression in yeast that can be used to construct and control naturally occurring and synthetic gene networks.

Protein assembly systems in natural and synthetic biology.

The traditional view of protein aggregation as being strictly disease-related has been challenged by many examples of cellular aggregates that regulate beneficial biological functions. When coupled with the emerging view that many regulatory proteins undergo phase separation to form dynamic cellular compartments, it has become clear that supramolecular assembly plays wide-ranging and critical roles in cellular regulation. This presents opportunities to develop new tools to probe and illuminate this biology, and to harness the unique properties of these self-assembling systems for synthetic biology for the purposeful manipulation of biological function.

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER.

Continuous culture methods enable cells to be grown under quantitatively controlled environmental conditions, and are thus broadly useful for measuring fitness phenotypes and improving our understanding of how genotypes are shaped by selection. Extensive recent efforts to develop and apply niche continuous culture devices have revealed the benefits of conducting new forms of cell culture control. This includes defining custom selection pressures and increasing throughput for studies ranging from long-term experimental evolution to genome-wide library selections and synthetic gene circuit characterization. The eVOLVER platform was recently developed to meet this growing demand: a continuous culture platform with a high degree of scalability, flexibility, and automation. eVOLVER provides a single standardizing platform that can be (re)-configured and scaled with minimal effort to perform many different types of high-throughput or multi-dimensional growth selection experiments. Here, a protocol is presented to provide users of the eVOLVER framework a description for configuring the system to conduct a custom, large-scale continuous growth experiment. Specifically, the protocol guides users on how to program the system to multiplex two selection pressures - temperature and osmolarity - across many eVOLVER vials in order to quantify fitness landscapes of Saccharomyces cerevisiae mutants at fine resolution. We show how the device can be configured both programmatically, through its open-source web-based software, and physically, by arranging fluidic and hardware layouts. The process of physically setting up the device, programming the culture routine, monitoring and interacting with the experiment in real-time over the internet, sampling vials for subsequent offline analysis, and post experiment data analysis are detailed. This should serve as a starting point for researchers across diverse disciplines to apply eVOLVER in the design of their own complex and high-throughput cell growth experiments to study and manipulate biological systems.

Modeling the impact of drug interactions on therapeutic selectivity.

Combination therapies that produce synergistic growth inhibition are widely sought after for the pharmacotherapy of many pathological conditions. Therapeutic selectivity, however, depends on the difference between potency on disease-causing cells and potency on non-target cell types that cause toxic side effects. Here, we examine a model system of antimicrobial compound combinations applied to two highly diverged yeast species. We find that even though the drug interactions correlate between the two species, cell-type-specific differences in drug interactions are common and can dramatically alter the selectivity of compounds when applied in combination vs. single-drug activity-enhancing, diminishing, or inverting therapeutic windows. This study identifies drug combinations with enhanced cell-type-selectivity with a range of interaction types, which we experimentally validate using multiplexed drug-interaction assays for heterogeneous cell cultures. This analysis presents a model framework for evaluating drug combinations with increased efficacy and selectivity against pathogens or tumors.

Precise, automated control of conditions for high-throughput growth of yeast and bacteria with eVOLVER.

Precise control over microbial cell growth conditions could enable detection of minute phenotypic changes, which would improve our understanding of how genotypes are shaped by adaptive selection. Although automated cell-culture systems such as bioreactors offer strict control over liquid culture conditions, they often do not scale to high-throughput or require cumbersome redesign to alter growth conditions. We report the design and validation of eVOLVER, a scalable do-it-yourself (DIY) framework, which can be configured to carry out high-throughput growth experiments in molecular evolution, systems biology, and microbiology. High-throughput evolution of yeast populations grown at different densities reveals that eVOLVER can be applied to characterize adaptive niches. Growth selection on a genome-wide yeast knockout library, using temperatures varied over different timescales, finds strains sensitive to temperature changes or frequency of temperature change. Inspired by large-scale integration of electronics and microfluidics, we also demonstrate millifluidic multiplexing modules that enable multiplexed media routing, cleaning, vial-to-vial transfers and automated yeast mating.

A Genetic Tool to Track Protein Aggregates and Control Prion Inheritance.

Protein aggregation is a hallmark of many diseases but also underlies a wide range of positive cellular functions. This phenomenon has been difficult to study because of a lack of quantitative and high-throughput cellular tools. Here, we develop a synthetic genetic tool to sense and control protein aggregation. We apply the technology to yeast prions, developing sensors to track their aggregation states and employing prion fusions to encode synthetic memories in yeast cells. Utilizing high-throughput screens, we identify prion-curing mutants and engineer "anti-prion drives" that reverse the non-Mendelian inheritance pattern of prions and eliminate them from yeast populations. We extend our technology to yeast RNA-binding proteins (RBPs) by tracking their propensity to aggregate, searching for co-occurring aggregates, and uncovering a group of coalescing RBPs through screens enabled by our platform. Our work establishes a quantitative, high-throughput, and generalizable technology to study and control diverse protein aggregation processes in cells.

Cellular Advantages to Signaling in a Digital World.

A newly revealed cellular strategy for modularizing function inspires engineers.

Using targeted chromatin regulators to engineer combinatorial and spatial transcriptional regulation.

The transcription of genomic information in eukaryotes is regulated in large part by chromatin. How a diverse array of chromatin regulator (CR) proteins with different functions and genomic localization patterns coordinates chromatin activity to control transcription remains unclear. Here, we take a synthetic biology approach to decipher the complexity of chromatin regulation by studying emergent transcriptional behaviors from engineered combinatorial, spatial, and temporal patterns of individual CRs. We fuse 223 yeast CRs to programmable zinc finger proteins. Site-specific and combinatorial recruitment of CRs to distinct intralocus locations reveals a range of transcriptional logic and behaviors, including synergistic activation, long-range and spatial regulation, and gene expression memory. Comparing these transcriptional behaviors with annotated CR complex and function terms provides design principles for the engineering of transcriptional regulation. This work presents a bottom-up approach to investigating chromatin-mediated transcriptional regulation and introduces chromatin-based components and systems for synthetic biology and cellular engineering.