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Systematic Mapping of Bacterial CRISPRa Systems for Synergistic Gene Activation Reveals Antagonistic Effects

CRISPR gene activation (CRISPRa) tools have shown great promise for bacterial strain engineering but often require customization for each intended application. Our goal is to create generalizable CRISPRa tools that can overcome previous limitations of gene activation in bacteria. In eukaryotic cells, multiple activators can be combined for synergistic gene activation. To identify potential effectors for synergistic activation in bacteria, we systematically characterized bacterial activator proteins with a set of engineered synthetic promoters. We found that optimal target sites for different activators could vary by up to 200 bases in the region upstream of the transcription start site (TSS). These optimal target sites qualitatively matched previous reports for each activator, but the precise targeting rules varied between different promoters. By characterizing targeting rules in the same promoter context, we were able to test activator combinations with each effector positioned at its optimal target site. We did not find any activator combinations that produced synergistic activation, and we found that many combinations were antagonistic. Furthermore, this systematic investigation highlights fundamental mechanistic differences between bacterial and eukaryotic transcriptional activation systems and suggests that alternative strategies will be necessary for strong bacterial gene activation at arbitrary endogenous targets.

CRISPR activation↗

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Towards engineering hybrid incompatibility in plants

The potential for gene flow between genetically modified organisms (GMOs) and non-GMO relatives poses a significant challenge to the development and regulatory approval of GMO crops (Wedger et al., 2024), for example, the spread of herbicide resistance transgenes from crops such as rice or sorghum to cross-pollinating weedy species. Addressing this concern, we developed Engineered Genetic Incompatibility (EGI) (Maselko et al., 2017), a system that establishes species-like barriers to gene flow between otherwise sexually compatible populations. EGI employs Programmable Transcriptional Activators (PTAs) to drive lethal over- and/or ectopic expression of tightly regulated genes following undesired hybridization events (Figure 1a,b). A benign mutation of the target promoter in the EGI organism protects it from ill effects of the PTA, which acts as a sentinel for the wild-type (WT) promoter sequence. Given numerous potential PTA targets, multiple mutually incompatible subpopulations are feasible (Maselko et al., 2020). EGI has been demonstrated in yeast as a proof-of-concept (Maselko et al., 2017) and in insects as a strategy for genetic biocontrol of pests (Maselko et al., 2020; Upadhyay et al., 2022). EGI in plants would provide a strategy to halt gene flow between engineered crops and their domestic and wild relatives without altering normal cultivation or propagation practices. Here, we present promising results towards the demonstration of EGI in plants and highlight technical challenges that still need to be overcome.

CRISPRa↗