ArticleACS synthetic biology2015
Direct mutagenesis of thousands of genomic targets using microarray-derived oligonucleotides.
Article in ACS synthetic biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- High-throughput editing boosts the construction of next-generation microbial cell factories.Synthetic and systems biotechnology · 2026Review
- Synthetic Biology of Plants and Microbes for Agriculture, Environment, and Future Applications.Chemical reviews · 2026Review
- Article
- ORBIT for E. coli: kilobase-scale oligonucleotide recombineering at high throughput and high efficiency.Nucleic acids research · 2024Article
- A primer to directed evolution: current methodologies and future directions.RSC chemical biology · 2023Review
- Oligo replication advantage driven by GC content and Gibbs free energy.Biotechnology letters · 2022Article
- Recombineering and MAGE.Nature reviews. Methods primers · 2021Article
- Targeted mutagenesis of multiple chromosomal regions in microbes.Current opinion in microbiology · 2020Review
- Dynamic control of endogenous metabolism with combinatorial logic circuits.Molecular systems biology · 2018Article
- Synthetic biology advances and applications in the biotechnology industry: a perspective.Journal of industrial microbiology & biotechnology · 2018Article
- Directed evolution of multiple genomic loci allows the prediction of antibiotic resistance.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- High throughput protease profiling comprehensively defines active site specificity for thrombin and ADAMTS13.Scientific reports · 2018Article
- Efficient engineering of chromosomal ribosome binding site libraries in mismatch repair proficient Escherichia coli.Scientific reports · 2017Article
- Balancing gene expression without library construction via a reusable sRNA pool.Nucleic acids research · 2017Article
- Assessing glycolytic flux alterations resulting from genetic perturbations in E. coli using a biosensor.Metabolic engineering · 2017Article
- Targeted mutagenesis: A sniper-like diversity generator in microbial engineering.Synthetic and systems biotechnology · 2017Review
- Optimizing complex phenotypes through model-guided multiplex genome engineering.Genome biology · 2017Article
- Systems Metabolic Engineering of Escherichia coli.EcoSal Plus · 2016Review
- Predictable tuning of protein expression in bacteria.Nature methods · 2016Article
- A highly precise and portable genome engineering method allows comparison of mutational effects across bacterial species.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Multiplex Automated Genome Engineering (MAGE) allows simultaneous mutagenesis of multiple target sites in bacterial genomes using short oligonucleotides. However, large-scale mutagenesis requires hundreds to thousands of unique oligos, which are costly to synthesize and impossible to scale-up by traditional phosphoramidite column-based approaches. Here, we describe a novel method to amplify oligos from microarray chips for direct use in MAGE to perturb thousands of genomic sites simultaneously. We demonstrated the feasibility of large-scale mutagenesis by inserting T7 promoters upstream of 2585 operons in E. coli using this method, which we call Microarray-Oligonucleotide (MO)-MAGE. The resulting mutant library was characterized by high-throughput sequencing to show that all attempted insertions were estimated to have occurred at an average frequency of 0.02% per locus with 0.4 average insertions per cell. MO-MAGE enables cost-effective large-scale targeted genome engineering that should be useful for a variety of applications in synthetic biology and metabolic engineering.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.