Encoding information on DNA using enzyme-created label patterns
Representing Information on DNA using Patterns Induced by Enzymatic Labeling
Information Theory
Summary
Storing information on DNA is a new way to keep data safe and dense. This paper shows how patterns made by special enzymes that label DNA can represent information like digital code. The authors created a system to model this labeling and made efficient ways to encode and decode data. They also studied the limits of how much data can be stored using this method. Their work links to special sequences that help with reliable coding.
What this means in practice
- •For biotechnology developers: Create DNA-based data storage systems by using enzyme-induced label patterns to encode and decode digital information efficiently and reliably.
- •For synthetic biology engineers: Design DNA molecules with specific labeling sites to carry encoded information using CRISPR-Cas9 guided enzymatic labels.
Authors
Daniella Bar-Lev, Eitan Yaakobi, Zohar Yakhini, Tuvi Etzion
Abstract
Enzymatic DNA labeling is a powerful tool with applications in biochemistry, molecular biology, biotechnology, medical science, and genomic research. This paper contributes to the evolving field of DNA-based data storage by presenting a formal framework for modeling DNA labeling in strings, specifically tailored for data storage purposes. Our approach involves a known DNA molecule as a template for labeling, employing patterns induced by a set of designed labels to represent information. One hypothetical implementation can use CRISPR-Cas9 and gRNA reagents for labeling. Various aspects of the general labeling channel, including fixed-length labels, are explored, and upper bounds on the maximum size of the corresponding codes are given. The study includes the development of an efficient encoder-decoder pair that is proven to be optimal in terms of maximum code size under specific conditions. The codewords for this framework are codesets, i.e., each codeword is a collection of a few labels. Of special interest are codes whose codesets contain fixed-length labels. Their construction and analysis are tied to de Bruijn sequences and constrained coding.