Sprecher
Beschreibung
Starting several decades ago, our digital revolution has resulted in a continuous and ongoing exponential increase in digital data being produced, with estimates indicating that this data will soon outpace the storage capacity of current technologies [1,2]. This impending data storage crisis has led researchers to investigate alternative storage methods. DNA has been proposed as a promising candidate due to its high data density, long term stability and low maintenance costs, and important advances in the field of DNA-based digital data storage have been observed in recent years [1,2]. However, DNA-based systems still suffer from several limitations in terms of cost and speed, with limited dynamic data operability and random access capabilities. Random access of information in particular is a key aspect to consider, with the ability to selectively retrieve the specific data of interest without having to read out the entire pool of information becoming increasingly important as the amount of data stored increases [3]. In order to address these needs, we have developed a system that utilizes nucleic acid-guided enzymatic reactions to improve the capacity for dynamic data operation and random access in DNA-based data storage solutions. For one such data operation, the reading operation, we implemented an in vitro transcription-based data read out approach with primer-based selectivity for improved random access, circumventing several of the limitations of previous approaches. This system builds on the utilization of single-stranded data encoding strands carrying a unique primer binding site acting as data ID, allowing the targets of interest to be selectively converted to double-stranded form enabling their read out through T7 RNA polymerase-based transcription.
References:
[1] Wang, S. et al. Advanced Materials, 36(6), 2307499, 2024
[2] Doricchi, A. et al. ACS Nano, 16(11), 17552–17571, 2022
[3] Zhou, Y. et al. ACS Applied Materials & Interfaces, 16(33), 43102–43113, 2024
