ArticleNature communications2022
Machine learning-coupled combinatorial mutagenesis enables resource-efficient engineering of CRISPR-Cas9 genome editor activities.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 39 citations in OpenAlex.
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- Harnessing synthetic biology for tetraterpenoid astaxanthin production: Recent advances and challenges.Synthetic and systems biotechnology · 2026Review
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- Highly Efficient Site-Specific and Cassette Mutagenesis of Plasmids Harboring GC-Rich Sequences.Cells · 2025Article
- Genome-wide CRISPR screens identify critical targets to enhance CAR-NK cell antitumor potency.Cancer cell · 2025Article
- High throughput screening of eukaryotic release factor 1 variants to enhance noncanonical amino acid incorporation.bioRxiv : the preprint server for biology · 2025Article
- Recent advances in CRISPR-based single-nucleotide fidelity diagnostics.Communications medicine · 2025Review
- Article
- Engineering a New Generation of Gene Editors: Integrating Synthetic Biology and AI Innovations.ACS synthetic biology · 2025Review
- Recent developments and future directions in point-of-care next-generation CRISPR-based rapid diagnosis.Clinical and experimental medicine · 2025Review
- Synergizing CRISPR-Cas9 with Advanced Artificial Intelligence and Machine Learning for Precision Drug Delivery: Technological Nexus and Regulatory Insights.Current gene therapy · 2025Review
- Quantifying Protein-Nucleic Acid Interactions for Engineering Useful CRISPR-Cas9 Genome-Editing Variants.Methods in molecular biology (Clifton, N.J.) · 2025Article
- P3a site-specific and cassette mutagenesis for seamless protein, RNA and plasmid engineering.Genes & cancer · 2025Article
- A conditional protein diffusion model generates artificial programmable endonuclease sequences with enhanced activity.Cell discovery · 2024Article
- AI in cellular engineering and reprogramming.Biophysical journal · 2024Review
- Machine intelligence accelerated design of conductive MXene aerogels with programmable properties.Nature communications · 2024Article
- Multiplex CRISPR-Cas Genome Editing: Next-Generation Microbial Strain Engineering.Journal of agricultural and food chemistry · 2024Review
- 'ChatGPT for CRISPR' creates new gene-editing tools.Nature · 2024Article
- Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models.Briefings in bioinformatics · 2023Review
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The genome-editing Cas9 protein uses multiple amino-acid residues to bind the target DNA. Considering only the residues in proximity to the target DNA as potential sites to optimise Cas9's activity, the number of combinatorial variants to screen through is too massive for a wet-lab experiment. Here we generate and cross-validate ten in silico and experimental datasets of multi-domain combinatorial mutagenesis libraries for Cas9 engineering, and demonstrate that a machine learning-coupled engineering approach reduces the experimental screening burden by as high as 95% while enriching top-performing variants by ∼7.5-fold in comparison to the null model. Using this approach and followed by structure-guided engineering, we identify the N888R/A889Q variant conferring increased editing activity on the protospacer adjacent motif-relaxed KKH variant of Cas9 nuclease from Staphylococcus aureus (KKH-SaCas9) and its derived base editor in human cells. Our work validates a readily applicable workflow to enable resource-efficient high-throughput engineering of genome editor's activity.
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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.