STAGE: A compact and versatile TnpB-based genome editing toolkit for <i>Streptomyces</i>
<i>Streptomyces</i> are naturally endowed with the capacity to produce a wide array of natural products with biomedical and biotechnological value. They have garnered great interest in synthetic biology applications given the abundance of uncharacterized biosynthetic gene clusters (BGCs). However, progress has been hindered by the limited availability of genetic tools for manipulating these bacteria. Several representative CRISPR-Cas systems have been established in <i>Streptomyces</i> to streamline experimental workflows and improve editing efficiency. Nevertheless, their broader applicability has been constrained by issues such as nuclease activity-related cytotoxicity and the large size of effector proteins. To address these challenges, we present <i>Streptomyces</i>-compatible TnpB-assisted genome editing (STAGE), a genetic toolkit based on ISDra2 TnpB, which is approximately one-third the size of Cas9 and enables precise, site-specific gene editing. We demonstrated that STAGE introduces genetic mutations with high efficiency and minimal off-target effects in two industrially important <i>Streptomyces</i> strains. Building on this platform, we developed STAGE-cBEST and STAGE-McBEST, enabling single and multiplexed C·G-to-T·A base editing, respectively, with editing efficiencies exceeding 75%. To further enhance performance, we engineered the ISDra2 TnpB system using an AI-assisted protein engineering framework, resulting in two variants that achieve nearly 100% genome editing efficiency. Additionally, through sequence homology analysis, we identified a TnpB ortholog from the same biological origin of ISDra2 TnpB, which also functions effectively as a gene editing tool. Our study establishes STAGE as a highly precise, programmable, and versatile genome editing platform for <i>Streptomyces</i>, paving the way for advanced genetic manipulation and synthetic biology applications in these industrially important bacteria.
Authors
- Zihan Yuan
- Natalie Chia (ORCID: https://orcid.org/0000-0002-7553-9268)
- Yaojun Tong (ORCID: https://orcid.org/0000-0003-4042-2462)
- Sihan Yang
- Pan Tan (ORCID: https://orcid.org/0000-0003-3919-5805)
- Sang Yup Lee (ORCID: https://orcid.org/0000-0003-0599-3091)
- Hong Liang (ORCID: https://orcid.org/0000-0001-6131-7181)
- Jing Luo
- Yuxi Qin
- Lingwen Zhang
Institutions
- Korea Advanced Institute of Science and Technology (KR)
- Shanghai Jiao Tong University (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Shanghai Advanced Research Institute (CN)
- Institute of Natural Science (KP)
- Shanghai Artificial Intelligence Laboratory (CN)
Publication Details
- Journal
- Proceedings of the National Academy of Sciences
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1073/pnas.2509146122
- Citations
- 6
- Primary Topic
- CRISPR and Genetic Engineering
- Type
- article
- Field-Weighted Citation Impact
- 4.84
Funders
- Science and Technology Commission of Shanghai Municipality
- State Key Laboratory of Microbial Metabolism
- Ministry of Science and ICT, South Korea
- National Key Research and Development Program of China