Metabolic EngineeringSynthetic BiologyPeer-reviewed journal article
CIFR (Clone-Integrate-Flip-out-Repeat): a toolset for iterative genome and pathway engineering of Gram-negative bacteria
Filippo Federici, Francesco LuppinoiD, Clara Aguilar-Vilar, Maria Eleni Mazaraki, Lars Boje Petersen, Linda L. AhoneniD, Pablo I. NikeliD
Abstract
Advances in genome engineering enable precise and customizable modifications of bacterial species. Toolsets for metabolic engineering that exhibit broad-host compatibility are particularly valued owing to their portability. Tn5 transposon vectors have been widely used to establish random integrations of desired DNA sequences into bacterial genomes. However, the iteration of the procedure remains challenging because of the limited availability of selection markers. Here, we present CIFR, a mini-Tn5 integration system for iterative genome engineering. The pCIFR vectors incorporate attP and attB sites flanking an antibiotic resistance marker used to select for the insertion. Subsequent removal of these antibiotic determinants is facilitated by the Bxb1 integrase, and a user-friendly counter-selection marker, both encoded in auxiliary plasmids. Hence, CIFR delivers engineered strains harboring stable DNA insertions and free of any antibiotic resistance cassette, allowing for the reusability of the tool. The system was validated in Pseudomonas putida, Escherichia coli, and Cupriavidus necator, underscoring its portability across diverse industrially-relevant hosts. The CIFR toolbox was calibrated through combinatorial integrations of chromoprotein genes in P. putida, generating strains displaying a diverse color palette. Next, we introduced a carotenoid biosynthesis pathway in P. putida in a two-step engineering process, showcasing the potential of the tool for pathway balancing. The broad utility of the toolbox expands the synthetic biology toolkit for metabolic engineering, allowing for the construction of complex phenotypes, while opening new possibilities in bacterial genetic manipulations.
- Citations
- 16
- FWCI
- 4.78
- Field percentile
- top 4%
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