Highly Secure In Vivo DNA Data Storage Driven by Genomic Dynamics
DNA is a promising medium for next-generation data storage because of ultrahigh information density and stability. DNA storage within living organisms presents further advantages, such as self-replication, compactness, and concealment. Early efforts primarily developed predetermined methods for encoding and decoding data using in vivo DNA sequences. However, these methods may pose a security risk while opening a clear channel for potential data access and breaches. To address these challenges, we propose a unified paradigm, integrated computational-biological programming (ICBP), by exploiting the intrinsic digital characteristics within computational and microbial systems. ICBP involves the construction of dynamic code tables from gene regulatory networks or complete genomes across diverse species, expanding the key space by more than 100 orders of magnitude compared with existing methods. The encryption algorithm in ICBP benefits from DNA encoding, computing, and computational operations, leading to superior encryption quality and resistance to brute force and statistical attacks. Furthermore, we demonstrated the practical utility of ICBP via the successful encryption, microbial storage, and decryption of digital files within living systems, achieving 100% data recovery after 100 generations of replication. By combining computational logic with the biological complexities of living systems, the ICBP offers a transformative strategy for secure DNA data storage.
Authors
- Shanze Chen
- Yu Wang
- Mingen Li
- Jiaxin Xu
- Yang Wang
- Lingwei Wang
- Junbiao Dai
- Xiaoluo Huang
- Haibo Zhou
- Hui Mei
Institutions
- Jinan University (CN)
- Chinese Academy of Sciences (CN)
- Agricultural Genomics Institute at Shenzhen (CN)
- Synthetic Genomics (United States) (US)
- Chinese Academy of Agricultural Sciences (CN)
- Southern Medical University Shenzhen Hospital (CN)
- Shenzhen Institutes of Advanced Technology (CN)
- Ministry of Agriculture and Rural Affairs (CN)
- Shenzhen Second People's Hospital (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2026-01-26
- DOI
- https://doi.org/10.1002/advs.202514565
- Primary Topic
- DNA and Biological Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- Chinese Academy of Agricultural Sciences
- National Key Research and Development Program of China