Advancements in DNA storage: innovations, challenges, and the road ahead

ABSTRACT

The enormous growth of digital data has increased the need for robust storage methods that offer more capacity and durability than traditional devices. DNA storage is a promising alternative that encodes information in the structure of deoxyribonucleic acid. This method uses the natural four-letter code of DNA, along with chemical modifications known as epibits, to achieve high density and long-lasting stability. Recent advances in enzymatic synthesis have lowered production costs significantly and boosted output, making the process more efficient. Machine learning techniques have been applied to improve data retrieval by reducing errors in synthesis and sequencing. Preservation strategies, including silica encapsulation and microcapsule technology, have been examined to maintain the stability of DNA over long periods. In addition, research on combining storage with computational functions in DNA offers ways to reduce energy use during data processing. This chapter provides a comprehensive review of these emerging trends. It outlines the latest methods for encoding digital information into DNA and discusses recent breakthroughs in synthesis techniques that lower costs and increase throughput. The discussion includes an evaluation of advanced retrieval methods that incorporate machine learning to enhance accuracy and speed. Preservation techniques aimed at protecting the integrity of DNA storage are also reviewed. Moreover, the chapter assesses the challenges involved in scaling up the technology to handle massive amounts of data, as well as the need for improved error correction mechanisms. Ethical and security issues, including data privacy and potential misuse, are addressed to highlight the broader implications of adopting this technology.