Composite Mapping for Peptide‐Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles

Peptides are natural information-bearing mediums and are promising for high-density data storage. However, conventional mapping of one amino acid (AA) to one binary code has limited the improvement of coding density by increasing the total number of different AAs. Here, a novel composite mapping strategy is developed, where each position in the peptide sequence is a composite letter consisting of several different AAs, and thousands of composite letters are available for mapping, thus breaking the limit of conventional mapping. When 20 different AAs are used, the coding density of six-AAs composite mapping achieves 15 bits/letter, while conventional mapping only reaches 4 bits/AA. The whole process of encoding data into composite letter sequences, synthesizing composite letter sequences via solid-phase peptide synthesis, sequencing composite letter sequences by mass spectrometry, and decoding data from composite letter sequences is successfully demonstrated for the first time. Composite mapping also demonstrates several distinct advantages, including high coding density, few synthesis cycles, high reliability against errors, low probability of homopolymers, and good compatibility with other encoding algorithms. The developed composite mapping strategy provides a novel way for peptide-based data storage to increase the coding density and reduce the synthesis cycles, showing great potential for large-scale data storage.

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Publication Details

Journal
Advanced Science
Published
2025-04-26
DOI
https://doi.org/10.1002/advs.202503790
Citations
5
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
4.03

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article

Composite Mapping for Peptide‐Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles

Ji‐Shen Zheng, Long-Jie Wang, Yongxi Zhao, Anxun Zhang et al.
5 citations
Advanced Science
DNA and Biological Computing
4.03
article

Composite Mapping for Peptide‐Based Data Storage with Higher Coding Density and Fewer Synthesis Cycles

Ji‐Shen Zheng, Long-Jie Wang, Yongxi Zhao, Anxun Zhang, Xiaowei Zhai, Dong Chen, Kai Liu, Yao Xiao, Yanchan Wu
article en
5 citations

Abstract

Peptides are natural information-bearing mediums and are promising for high-density data storage. However, conventional mapping of one amino acid (AA) to one binary code has limited the improvement of coding density by increasing the total number of different AAs. Here, a novel composite mapping strategy is developed, where each position in the peptide sequence is a composite letter consisting of several different AAs, and thousands of composite letters are available for mapping, thus breaking the limit of conventional mapping. When 20 different AAs are used, the coding density of six-AAs composite mapping achieves 15 bits/letter, while conventional mapping only reaches 4 bits/AA. The whole process of encoding data into composite letter sequences, synthesizing composite letter sequences via solid-phase peptide synthesis, sequencing composite letter sequences by mass spectrometry, and decoding data from composite letter sequences is successfully demonstrated for the first time. Composite mapping also demonstrates several distinct advantages, including high coding density, few synthesis cycles, high reliability against errors, low probability of homopolymers, and good compatibility with other encoding algorithms. The developed composite mapping strategy provides a novel way for peptide-based data storage to increase the coding density and reduce the synthesis cycles, showing great potential for large-scale data storage.

Advanced ScienceVol. 12(27)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Changchun Institute of Applied Chemistry (CN), Quzhou University (CN), Zhejiang University (CN), Xi'an Jiaotong University (CN), Tsinghua University (CN)
National Natural Science Foundation of China, University of Science and Technology of China, School of Life Sciences and Biotechnology Division of Life Sciences, Korea University
Openalex Percentile: Top 6%
DNA and Biological Computing
4.03
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