Random access and semantic search in DNA data storage enabled by Cas9 and machine-guided design
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View abstract on PubMed
Summary
This summary is machine-generated.CRISPR-Cas9 enables fast, selective DNA data retrieval for digital storage. This method simplifies data access and reduces costs, paving the way for efficient molecular data extraction.
Area Of Science
- Biotechnology
- Bioinformatics
- Molecular Biology
Background
- DNA offers high data density and longevity for digital storage.
- Efficient data retrieval is crucial for practical DNA storage systems.
- Current methods for molecular data extraction can be complex and time-consuming.
Purpose Of The Study
- To introduce CRISPR-Cas9 as a tool for multiplexed, low-latency molecular data extraction.
- To develop a user-friendly system for selective data retrieval from DNA.
- To enable efficient searching and retrieval of data stored in DNA.
Main Methods
- Developed a one-pot, multiplexed random access method using CRISPR-Cas9 for targeted DNA cleavage.
- Utilized nanopore sequencing for data retrieval after CRISPR-Cas9 cleavage.
- Combined machine learning (deep neural network) with Cas9-based retrieval for molecular similarity search.
Main Results
- Validated the CRISPR-Cas9 approach on 1.6 million DNA sequences (25 unique data files).
- Successfully mapped 1.74 million images into a reduced-dimensional embedding encoded as Cas9 target sequences.
- Demonstrated high-fidelity retrieval of molecular addresses for semantically related image clusters using Cas9's off-target activity.
Conclusions
- CRISPR-Cas9 provides a simplified and rapid method for DNA data retrieval.
- The developed approaches enhance molecular data access capabilities.
- These advancements address key challenges in DNA-based data storage and retrieval.
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