Autorepression-Based Conditional Gene Expression System in Yeast for Variation-Suppressed Control of Protein Dosage.

Conditional control of gene expression allows an experimenter to investigate many aspects of a gene's function. In the model organism Saccharomyces cerevisiae, a number of methods to control gene expression are widely practiced, including induction by metabolites, small molecules, and even light. However, all current methods suffer from at least one of a set of drawbacks, including need for specialized growth conditions, leaky expression, or requirement of specialized equipment. Here we describe protocols using two transformations to construct strains that carry a new controller in which all these drawbacks are overcome. In these strains, the expression of a controlled gene of interest is repressed by the bacterial repressor TetR and induced by anhydrotetracycline. TetR also regulates its own expression, creating an autorepression loop. This autorepression allows tight control of gene expression and protein dosage with low cell-to-cell variation in expression. A second repressor, TetR-Tup1, prevents any leaky expression. We also present a protocol showing a particular workhorse application of such strains to generate synchronized cell populations. We turn off expression of the cell cycle regulator CDC20 completely, arresting the cell population, and then we turn it back on so that the synchronized cells resume cell cycle progression. This control system can be applied to any endogenous or exogenous gene for precise expression. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Generating a parent WTC846 strain Basic Protocol 2: Generating a WTC846 strain with controlled expression of the targeted gene Alternate Protocol: CRISPR-mediated promoter replacement Basic Protocol 3: Cell cycle synchronization/arrest and release using the WTC846- K3 ::CDC20 strain.

DeepSARS: simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2.

BACKGROUND: The continued spread of SARS-CoV-2 and emergence of new variants with higher transmission rates and/or partial resistance to vaccines has further highlighted the need for large-scale testing and genomic surveillance. However, current diagnostic testing (e.g., PCR) and genomic surveillance methods (e.g., whole genome sequencing) are performed separately, thus limiting the detection and tracing of SARS-CoV-2 and emerging variants. RESULTS: Here, we developed DeepSARS, a high-throughput platform for simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 by the integration of molecular barcoding, targeted deep sequencing, and computational phylogenetics. DeepSARS enables highly sensitive viral detection, while also capturing genomic diversity and viral evolution. We show that DeepSARS can be rapidly adapted for identification of emerging variants, such as alpha, beta, gamma, and delta strains, and profile mutational changes at the population level. CONCLUSIONS: DeepSARS sets the foundation for quantitative diagnostics that capture viral evolution and diversity. DeepSARS uses molecular barcodes (BCs) and multiplexed targeted deep sequencing (NGS) to enable simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2. Image was created using Biorender.com .

A precisely adjustable, variation-suppressed eukaryotic transcriptional controller to enable genetic discovery.

Conditional expression of genes and observation of phenotype remain central to biological discovery. Current methods enable either on/off or imprecisely controlled graded gene expression. We developed a 'well-tempered' controller, WTC846, for precisely adjustable, graded, growth condition independent expression of genes in Saccharomyces cerevisiae. Controlled genes are expressed from a strong semisynthetic promoter repressed by the prokaryotic TetR, which also represses its own synthesis; with basal expression abolished by a second, 'zeroing' repressor. The autorepression loop lowers cell-to-cell variation while enabling precise adjustment of protein expression by a chemical inducer. WTC846 allelic strains in which the controller replaced the native promoters recapitulated known null phenotypes (CDC42, TPI1), exhibited novel overexpression phenotypes (IPL1), showed protein dosage-dependent growth rates and morphological phenotypes (CDC28, TOR2, PMA1 and the hitherto uncharacterized PBR1), and enabled cell cycle synchronization (CDC20). WTC846 defines an 'expression clamp' allowing protein dosage to be adjusted by the experimenter across the range of cellular protein abundances, with limited variation around the setpoint.

Controlling cell-to-cell variability with synthetic gene circuits.

Cell-to-cell variability originating, for example, from the intrinsic stochasticity of gene expression, presents challenges for designing synthetic gene circuits that perform robustly. Conversely, synthetic biology approaches are instrumental in uncovering mechanisms underlying variability in natural systems. With a focus on reducing noise in individual genes, the field has established a broad synthetic toolset. This includes noise control by engineering of transcription and translation mechanisms either individually, or in combination to achieve independent regulation of mean expression and its variability. Synthetic feedback circuits use these components to establish more robust operation in closed-loop, either by drawing on, but also by extending traditional engineering concepts. In this perspective, we argue that major conceptual advances will require new theory of control adapted to biology, extensions from single genes to networks, more systematic considerations of origins of variability other than intrinsic noise, and an exploration of how noise shaping, instead of noise reduction, could establish new synthetic functions or help understanding natural functions.