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Updated: May 11, 2026
Standardized Modular Assembly of Polycistronic Operons with Modular Cloning (MoClo) using the In-Cloning toolkit
Published on: September 2, 2025
Cloning large gene clusters from E. coli using in vitro single-strand overlapping annealing.
Rui-Yan Wang1, Zhen-Yu Shi, Jin-Chun Chen
1MOE Key Lab of Bioinformatics and Systems Biology, Department of Biological Science and Biotechnology, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China.
We developed a cost-effective gene cluster extraction method using in vitro single-strand overlapping annealing (SSOA). This technique enables efficient cloning of large DNA fragments from bacterial genomes, offering an alternative to chemical synthesis.
Area of Science:
- Molecular Biology
- Genomics
- Biotechnology
Background:
- Constructing large gene clusters from DNA fragments is challenging and costly.
- Existing methods for genomic DNA manipulation have limitations in scale and expense.
Purpose of the Study:
- To develop a novel, cost-effective method for extracting and cloning large gene clusters.
- To overcome the difficulties associated with current DNA synthesis and assembly techniques.
Main Methods:
- Developed an in vitro single-strand overlapping annealing (SSOA) method.
- Involves digesting target gene clusters, recovering fragments, and annealing single-strand DNA overhangs.
- Cloning into circular and linear vectors using specific annealing and covalent joining.
Main Results:
- Successfully cloned an 18 kb DNA fragment encoding NADH:ubiquinone oxidoreductase.
- Demonstrated cloning efficiency across various genomic DNA fragment sizes (11.86–55.99 kb).
- The SSOA method is effective for cloning regions up to approximately 28 kb in E. coli genomes.
Conclusions:
- The SSOA method offers a practical and economical approach for gene cluster construction.
- This technique serves as a valuable alternative to chemically synthesized gene clusters for genome assembly.
- Integration with KEGG and KEIO strain data enhances its utility for E. coli genome analysis.
