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Abstract Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas genome-wide screens are powerful tools for unraveling genotype–phenotype relationships, enabling precise manipulation of genes to study and engineer industrially useful traits. Traditional genetic methods, such as random mutagenesis or RNA interference, often lack the specificity and scalability required for large-scale functional genomic screens. CRISPR systems overcome these limitations by offering precision gene targeting and manipulation, allowing for high-throughput investigations into gene function and interactions. Recent work has shown that CRISPR genome editing is widely adaptable to several yeast species, many of which have natural traits suited for industrial biotechnology. In this review, we discuss recent advances in yeast functional genomics, emphasizing advancements made with CRISPR tools. We discuss how the development and optimization of CRISPR genome-wide screens have enabled a host-first approach to metabolic engineering, which takes advantage of the natural traits of nonconventional yeast—fast growth rates, high stress tolerance, and novel metabolism—to create new production hosts. Lastly, we discuss future directions, including automation and biosensor-driven screens, to enhance high-throughput CRISPR-enabled yeast engineering. 

Monoterpenes are valued for their roles as flavors, fragrances, insecticides, and energy-dense fuels. Microorganisms provide sustainable biosynthesis routes for these important molecules, but production levels remain limited. Here, we introduce a biosensor-driven microbial engineering strategy to enhance monoterpene production, specifically targeting geraniol. Using mutagenized libraries of the PYR1 receptor─a versatile biosensor from plant ABA signaling pathways with a malleable binding pocket─we screened 24 monoterpenes and identified PYR1 variants responsive to eight, including geraniol. A low background, highly selective geraniol-sensitive PYR1 variant was expressed in the thermotolerant yeast Kluyveromyces marxianus as a growth-based biosensor circuit, allowing for rapid strain engineering. By coupling the geraniol-sensitive PYR1 sensor with a genome-wide CRISPR-Cas9 mutagenesis approach, we identified six gene knockouts that enhance geraniol production, achieving up to a 2-fold increase in titer. This study demonstrates the power of the PYR1 biosensor platform to enable rapid strain engineering and the identification of mutants that improve the titer of a desired metabolite. 

Designing CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) single guide RNA (sgRNA) libraries targeting entire kingdoms of life will significantly advance genetic research in diverse and underexplored taxa. Current sgRNA design tools are often species-specific and fail to scale to large, phylogenetically diverse datasets, limiting their applicability to comparative genomics, evolutionary studies, and biotechnology. Here, we introduce ALLEGRO, a combinatorial optimization algorithm designed to compose minimal, yet highly effective sgRNA libraries targeting thousands of species at the same time. Leveraging integer linear programming, ALLEGRO identified compact sgRNA sets simultaneously targeting multiple genes of interest for over 2000 species across the fungal kingdom. We experimentally validated sgRNAs designed by ALLEGRO in Kluyveromyces marxianus, Komagataella phaffii, Yarrowia lipolytica, and Saccharomyces cerevisiae, confirming successful genome edits. Additionally, we employed a generalized Cas9–ribonucleoprotein delivery system to apply ALLEGRO’s sgRNA libraries to untested fungal genomes, such as Rhodotorula araucariae. Our experimental findings, together with cross-validation, demonstrate that ALLEGRO facilitates efficient CRISPR genome editing, enabling the development of universal sgRNA libraries applicable to entire taxonomic groups. 

Abstract   The multifaceted nature of CRISPR screens has propelled advancements in the field of functional genomics. Pooled CRISPR screens involve creating programmed genetic perturbations across multiple genomic sites in a pool of host cells subjected to a challenge, empowering researchers to identify genetic causes of desirable phenotypes. These genome-wide screens have been widely used in mammalian cells to discover biological mechanisms of diseases and drive the development of targeted drugs and therapeutics. Their use in non-model organisms, especially in microbes to improve bioprocessing-relevant phenotypes, has been limited. Further compounding this issue is the lack of bioinformatic algorithms for analyzing microbial screening data with high accuracy. Here, we describe the general approach and underlying principles for conducting pooled CRISPR knockout screens in non-conventional yeasts and performing downstream analysis of the screening data, while also reviewing state-of-the-art algorithms for identification of CRISPR screening outcomes. Application of pooled CRISPR screens to non-model yeasts holds considerable potential to uncover novel metabolic engineering targets and improve industrial bioproduction. One-Sentence Summary This mini-review describes experimental and computational approaches for functional genomic screening using CRISPR technologies in non-conventional microbes.