Long-stranded XNA-cssDNA hybrids for robust data storage

Area of Science:

• Biotechnology
• Synthetic Biology
• Data Storage

Background:

• DNA offers high-density, low-energy data storage potential.
• Long-stranded DNA storage faces stability challenges.
• Xeno nucleic acids (XNA) present an alternative for enhanced stability.

Purpose of the Study:

• To develop a robust DNA-based data storage system.
• To improve the stability and synthesis of DNA for data storage.
• To achieve high-fidelity data writing and reading.

Main Methods:

• A long-stranded xeno nucleic acid-circular single-stranded DNA (XNA-cssDNA) hybrid strategy was developed.
• 2'-fluoro-arabinonucleic acid (FANA) was identified as the optimal XNA.
• A temperature-guided language model evolved a faster FANA polymerase (Tgo^mut) for synthesizing long strands (>7500 nt).
• Data was encoded onto cssDNA using M13 bacteriophage.

Main Results:

• FANA-cssDNA hybrids demonstrated significant resistance to chemical and enzymatic degradation.
• The evolved Tgo^mut polymerase showed a ~4.4-fold increase in speed compared to Tgo^D4K.
• A dual-strategy framework achieved 100% data recovery, even after DNA degradation.
• Encoded digital data and a gene were successfully visualized in mammalian cells.

Conclusions:

• The FANA-cssDNA hybrid strategy significantly enhances DNA data storage robustness.
• Engineered polymerases overcome synthesis limitations, enabling longer DNA strands for data encoding.
• This approach offers a stable and reliable method for DNA data storage and retrieval, with potential for in-cell data applications.