ArticleACS synthetic biology2026
Tandem-sgRNA Provides an Effective Reverse Genetic Approach for Suppression of Streptomyces Biosynthetic Gene Clusters and Secondary Metabolism.
Article in ACS synthetic biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Bacterial biosynthetic gene clusters (BGCs) encode secondary metabolites with diverse biological activities; however, most BGC products remain uncharacterized. One approach to identifying products and their metabolism is to use reverse genetics to identify metabolite-associated phenotypes. CRISPR interference (CRISPRi) offers a promising approach to disrupt BGC functions in high-GC genomes, typical of Streptomyces species. In many of these organisms, single-guide RNA (sgRNA)-mediated CRISPRi often results in incomplete product suppression, resulting in partial phenotypes that are unsuitable for functional studies. Using Streptomyces sp. Mg1, we found that a tandem-sgRNA configuration for CRISPRi improved the efficiency of target metabolite suppression. We engineered strains to express two sgRNAs to target the same promoter region within a BGC, resulting in greater than 80% metabolite suppression across diverse secondary metabolite classes. We used tandem-sgRNA CRISPRi to identify phenotypes associated with the loss of polyketide linearmycins, the siderophore desferrioxamine, the terpene β-carotene, and an uncharacterized nonribosomal peptide synthetase (NRPS). This approach revealed that β-carotene depletion substantially reduced intrinsic cellular autofluorescence. Targeting the unknown NRPS produced developmental phenotypes and enabled the identification of the biosynthetic genes for the antibiotic lavendomycin, revealing a noncollinear organization of genes in the BGC. We suggest that tandem-sgRNA CRISPRi provides an efficient reverse genetics platform for the functional characterization of Streptomyces BGCs, enabling the correlation of metabolites with the gene function, identification of associated phenotypes, and prioritization of cryptic BGCs for natural product discovery.
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