Lijia Jia, Yue Shi, Jing Yang, Shangzhe Li, Wenjing Yang, Wei Li, Mancang Zhang, Quanshun Li, Yifei Zhang, Xiaolin Wang, Lin Li, Bo Duan, Dongbo Bu, Fei Chen, Haizhou Liu, Huaiyi Yang, Yongyong Shi, Di Liu
{"title":"DNA Data Storage Architecture via Ligation of Dynamic DNA Bytes","authors":"Lijia Jia, Yue Shi, Jing Yang, Shangzhe Li, Wenjing Yang, Wei Li, Mancang Zhang, Quanshun Li, Yifei Zhang, Xiaolin Wang, Lin Li, Bo Duan, Dongbo Bu, Fei Chen, Haizhou Liu, Huaiyi Yang, Yongyong Shi, Di Liu","doi":"10.1002/smtd.202502001","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The explosive growth of digital data is overwhelming conventional storage media, creating an urgent need for more efficient solutions. DNA, with its ultra-high density and long-term stability, emerges as a promising medium; however, most current implementations remain static and archival, limiting practical utility. To address this limitation, a modular DNA data storage system built upon dynamic DNA bytes (DynaBytes)—pre-fabricated DNA segments that can be ligated into reconfigurable information units—is presented. Within this DynaByte system, core, functional, and control DynaBytes are organized to implement a molecular file system, enabling the storage of 210,776 bits (26,347 bytes) of digital information with demonstrated CRUD (Create-Read-Update-Delete)-like operations, hierarchical access, and nanopore-based real-time retrieval. Robust data recovery is achieved under ∼100x error-prone sequencing through streamlined error correction and fuzzy decoding. By relying on in vitro ligation of standardized components, the DynaByte system reduces cost, scales efficiently, and supports interactive, rewritable data storage. These features advance DNA storage beyond passive archiving toward a reconfigurable framework, opening new possibilities for dynamic, practical, and large-scale DNA-based data systems.</p>\n </div>","PeriodicalId":229,"journal":{"name":"Small Methods","volume":"10 13","pages":""},"PeriodicalIF":8.7000,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Small Methods","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/smtd.202502001","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/31 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The explosive growth of digital data is overwhelming conventional storage media, creating an urgent need for more efficient solutions. DNA, with its ultra-high density and long-term stability, emerges as a promising medium; however, most current implementations remain static and archival, limiting practical utility. To address this limitation, a modular DNA data storage system built upon dynamic DNA bytes (DynaBytes)—pre-fabricated DNA segments that can be ligated into reconfigurable information units—is presented. Within this DynaByte system, core, functional, and control DynaBytes are organized to implement a molecular file system, enabling the storage of 210,776 bits (26,347 bytes) of digital information with demonstrated CRUD (Create-Read-Update-Delete)-like operations, hierarchical access, and nanopore-based real-time retrieval. Robust data recovery is achieved under ∼100x error-prone sequencing through streamlined error correction and fuzzy decoding. By relying on in vitro ligation of standardized components, the DynaByte system reduces cost, scales efficiently, and supports interactive, rewritable data storage. These features advance DNA storage beyond passive archiving toward a reconfigurable framework, opening new possibilities for dynamic, practical, and large-scale DNA-based data systems.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.