Integrated Microfluidic DNA Storage Platform with Automated Sample Handling and Physical Data Partitioning.
Yuan Luo1,2,3, Shuchen Wang1,2, Zhuowei Feng1,2
1Shenzhen Key Laboratory of Smart Healthcare Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, No 1088, Xueyuan Rd., Xili, Nanshan District, Shenzhen 518055, Guangdong, P. R. China.
Analytical Chemistry
|September 15, 2022
Summary
This study introduces a microfluidic platform for automated DNA data storage and retrieval. The system enhances data integration and process automation, overcoming limitations of current tube-based methods for digital information storage.
Area of Science:
- Biotechnology
- Digital Information Storage
- Microfluidics
Background:
- Biopolymers, particularly DNA, offer a promising medium for digital information storage.
- Current DNA data storage methods often lack system integration and automation, relying on cumbersome tube/vial systems.
Purpose of the Study:
- To develop a microfluidic platform for automated storage and retrieval of data-encoding oligonucleotides.
- To enhance system integration and process automation in DNA data storage workflows.
Main Methods:
- Implementation of a microfluidic platform with a microvalve network architecture.
- Utilizing individually addressable compartments for orthogonal data partitioning and file indexing.
- Coupling the platform with nanopore sequencing for data recovery.
Main Results:
- Demonstrated automated storage and retrieval of data-encoding oligonucleotide samples.
- Achieved high data density: 9.5 TB per 4 × 2 mm² area.
- Successfully recovered stored files using nanopore sequencing, confirming data integrity.
Conclusions:
- The microfluidic platform significantly enhances function integration and process automation for DNA data storage.
- This approach represents a substantial advancement over existing microfluidic methods for digital data archiving.
- The platform offers a scalable and efficient solution for the future of high-density data storage.
