Presentation Information
[P03-326]Dual-Orthogonal CRISPR Screening to Identify Trait-Associated Targets for Engineering Robust Industrial Microorganisms
○Xue Zhang2,1, Kai Li1, Fengwu Bai1, Shen Hu2 (1. Shanghai Jiao Tong University (China), 2. Yangtze Delta Region Institute of Tsinghua University (China))
Keywords:
Dual-orthogonal CRISPR,Genome-wide screening,Cas13,Multi-stress tolerance,Synthetic biology,Saccharomyces cerevisiae,Corynebacterium glutamicum
[Purpose]
Industrial microorganisms frequently encounter combinatorial stresses during bioprocessing, including organic acids, furan derivatives, and product accumulation. Engineering robust strains remains challenging due to the polygenic and network-level nature of stress responses. While multi-omics approaches reveal global patterns, they often lack causal resolution, and conventional CRISPR screening is typically limited to single regulatory layers. Here, we aim to establish a dual-orthogonal CRISPR framework for causal and scalable identification of genetic determinants underlying complex stress tolerance across microbial hosts.
[Method]
The platform integrates dCas9-based and dCas13-mediated transcriptional and translational perturbation (CRISPRa/CRISPRi), respectively, which enables parallel perturbation at DNA and RNA levels. Genome-scale libraries targeting coding genes and regulatory elements were constructed and subjected to pooled selection under representative stress conditions. Sequencing-based enrichment analysis was combined with systems-level data integration for candidate prioritization.
[Results]
We first developed a genome-wide Cas13 gRNA design pipeline that enables high-throughput and scalable guide generation, with particular applicability to non-model microorganisms. Using this tool, we completed the design and construction of large-scale gRNA libraries (e.g., ~32,000 and ~16,000 guides for S. cerevisiae and C. glutamicum, respectively), and successfully established pooled microbial populations carrying dual-orthogonal CRISPR editors.Initial characterization of these pooled libraries suggested distinct growth and adaptation profiles under multiple stress conditions, indicating that the platform can capture population-level fitness dynamics in complex environments. Genome-wide screening suggested a set of candidate targets potentially associated with complex traits such as multi-stress tolerance. Importantly, integration with multi-omics data significantly improved target prioritization and reduced false positives. Ongoing work focuses on systematic validation and combinatorial optimization of prioritized targets.
[Conclusion]
This study establishes a dual-orthogonal CRISPR screening framework that integrates genome-wide perturbation with systems biology analysis to dissect complex phenotypes. The platform is broadly applicable to diverse microorganisms, including non-model industrial strains, and provides a generalizable strategy for accelerating the development of robust cell factories under industrial stress conditions.
Industrial microorganisms frequently encounter combinatorial stresses during bioprocessing, including organic acids, furan derivatives, and product accumulation. Engineering robust strains remains challenging due to the polygenic and network-level nature of stress responses. While multi-omics approaches reveal global patterns, they often lack causal resolution, and conventional CRISPR screening is typically limited to single regulatory layers. Here, we aim to establish a dual-orthogonal CRISPR framework for causal and scalable identification of genetic determinants underlying complex stress tolerance across microbial hosts.
[Method]
The platform integrates dCas9-based and dCas13-mediated transcriptional and translational perturbation (CRISPRa/CRISPRi), respectively, which enables parallel perturbation at DNA and RNA levels. Genome-scale libraries targeting coding genes and regulatory elements were constructed and subjected to pooled selection under representative stress conditions. Sequencing-based enrichment analysis was combined with systems-level data integration for candidate prioritization.
[Results]
We first developed a genome-wide Cas13 gRNA design pipeline that enables high-throughput and scalable guide generation, with particular applicability to non-model microorganisms. Using this tool, we completed the design and construction of large-scale gRNA libraries (e.g., ~32,000 and ~16,000 guides for S. cerevisiae and C. glutamicum, respectively), and successfully established pooled microbial populations carrying dual-orthogonal CRISPR editors.Initial characterization of these pooled libraries suggested distinct growth and adaptation profiles under multiple stress conditions, indicating that the platform can capture population-level fitness dynamics in complex environments. Genome-wide screening suggested a set of candidate targets potentially associated with complex traits such as multi-stress tolerance. Importantly, integration with multi-omics data significantly improved target prioritization and reduced false positives. Ongoing work focuses on systematic validation and combinatorial optimization of prioritized targets.
[Conclusion]
This study establishes a dual-orthogonal CRISPR screening framework that integrates genome-wide perturbation with systems biology analysis to dissect complex phenotypes. The platform is broadly applicable to diverse microorganisms, including non-model industrial strains, and provides a generalizable strategy for accelerating the development of robust cell factories under industrial stress conditions.
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