Linked data storage using DNA origami nanostructures

Domain: physics
Published: 2025-12-17
Editorial outcome: major_revision

Abstract
DNA-based storage is an alternative solution for archiving vast cold data. Its future development aims to meet the demands of hot data storage, which requires rapid random access and efficient data modification. Here, we present a DNA origami nanostructure-enabled linked data storage (DONLDS) system that implements a linked list architecture. This system uses distinct DNA origami shapes as nodes to store diverse data (English letters, numerals, Chinese characters) in binary locations, achieving a storage density of 222.22 Gbit/cm2. Pointers, defined by DNA strands at the nanostructure edges, establish data positions. Furthermore, detachable DNA strands serve as instructions, enabling dynamic linking of pointers for accurate storage and their reversible detachment for dynamic data retrieval. The DONLDS system eliminates the need for full-structure traversal, enables parallel data storage, and supports data insertion and removal. This highlights its adaptability and accuracy in managing complex datasets.

Introduction
DNA, serving as the fundamental material for carrying and transmitting information in organisms, exhibits information storage capacity and stability1–7. DNA storage technology typically employs synthetically engineered DNA sequences to store data, necessitating data to be written and read in a predetermined sequence8–10. With the development of advanced DNA synthesis and sequencing techniques, DNA storage is encompassing terabytes of text, audio, and image information which is characterized by high storage density, minimal electromagnetic interference, and reduced risk of data loss. This characteristic renders current DNA storage technologies particularly adept at preserving cold data (data accessed infrequently, prioritizing high-density, long-term archival)11–14. However, the future trajectory of DNA storage is to preserve hot data (data requiring frequent, rapid access and modification), encompassing rapid random access and effective data modification functionalities that current DNA synthesis-based sequential storage cannot perform15–20. Hence, researchers have delved into myriad innovative methods to enable data modification without synthesis. For instance, leveraging single-stranded DNA overhang sequences that bind primers at room temperature allows users to rename, delete, or lock files21. Additionally, some methods utilize natural DNA strands as information carriers, such as DNA punch cards22 or nanopore sensor-based DNA hard drives23,24. Despite offering alternative pathways, these methods often necessitate the redistribution and reorganization of entire storage units, resulting in significant data migration and processing overhead.

Linked storage, different to sequential storage in computer memory storage paradigms, effectively manages frequent data insertions and deletions by adjusting the pointers of storage nodes, thereby avoiding extensive data migration, thereby substantially reducing the complexity of data processing. To achieve DNA-based linked storage, nodes for storage and pointers for data migration are needed. Previous studies have proved that DNA origami nanostructures25, fabricated by a long scaffold DNA with numerous short staple DNA strands, not only inherit the encoding capacity26,27 for storage but have shape identifiability28–31, unparalleled addressability32–35 and structural controllability36–38. For instance, the DNA PAINT technology29 was employed to read information via spot arrays and reconfigurable DNA origami structures39,40 to achieve data changes at the molecular level. As an information storage medium, DNA origami holds significant potential to meet the demands of large-scale data storage and processing, poised to play a crucial role in the future of information science. Nevertheless, information storage based on DNA nanostructures, involving the specific identification and efficient reversible recombination of storage units for data modification and deletion, has yet to be explored.

Here, we have developed a DNA origami nanostructure-enabled linked data storage (DONLDS) system to create nodes, pointers, and operations for data traversal, insertion, and deletion. These nodes are fabricated by triangular, rectangular, and cross-shaped DNA origami nanostructures (DONs) with binary locations represented for English letters, Arabic numerals, and Chinese characters, the storage density of which reach 222.22 Gbit/cm2. Pointers are featured by a series of DNA strands at the edges of DONs for the definition of data position. The precise manipulation of data can be achieved through a series of detachable DNA strands, which are not only capable of performing connection operations to tightly integrate the nodes, thereby guaranteeing the high fidelity of data storage, but also adept at executing disconnection operations to sever the inter-node bonds, thereby facilitating the dynamic storage and retrieval of data. The durability and reusability of these data connections have been validated through repeated detachment and reattachment tests. Furthermore, we have demonstrated the ability of a linked list based on DONs to store the string ‘DNA helix 1953’ and edit it with data deletions and insertions for its transformation to ‘DNA storage 1988’. The flexible, efficient, and scalable DONLDS eliminates the traversal of the entire data structure, facilitates the parallel storage of diverse data types and supports the seamless insertion and removal of data, highlighting its adaptability and accuracy in managing complex datasets.

Results
Creation of the linked list in the DONLDS system
The linked storage employs nodes as its fundamental units, interconnected through pointers to forge an adaptable data chain. Each node encompasses not only data but also pointers directed towards adjacent nodes, thereby ensuring data continuity. Benefitting from the programmability and the self-assembly properties of DNA molecules. In DONLDS system, we utilized triangular, rectangular, and cross-shaped DNA origami nanostructure (TDON, RDON, CDON) as nodes, each of which had two sets of pointers. Typically, DONs with defined shape were fabricated by a long scaffold and hundreds of staple strands (Fig. 1a and Supplementary Fig. 1). To establish precise and orderly connections between nodes, we designed a series of strands with specific sequences as pointers, which were situated at the edges of DON nodes and adorned with grouping sequence coding (Supplementary Table 5). Furthermore, we introduced DNA strands as instructions to exercise exact control over the sequence for node connections. The sequences of the operation strands were meticulously crafted to be the reverse complement of the target pointer strands, ensuring a 16-nucleotide complementary base pairing between each pair of pointer and operation strands, thereby guaranteeing the specificity and stability of node connections (Fig. 1b). We assessed orthogonality among the 120 designed 16-nt pointer strands (Supplementary Table 5) by computing all pairwise Hamming distances. Visualization of the similarity matrix (Supplementary Fig. 3) showed that more than 99.27% of off-diagonal pairs scored ≤8 (<50% similarity), demonstrating low inter-sequence similarity and cross-reactivity risk across the design. Unlike traditional memory allocation, DONLDS system did not require contiguous memory nodes for data storage but dynamically allocates space at various locations in memory based on the size and type of data (Supplementary Fig. 2). This dynamic allocation and non-continuous storage approach allowed the system to flexibly accommodate fluctuations in data volume, obviating the need to reserve space for fixed-size data blocks. For example, to store 1 Kbit of data, we divide the data into 10 layers, and each layer requires 100–144 types of pointer strands and operation strands (Supplementary Table 1). Atomic force microscopy (AFM) images illustrated how nodes of varying shapes achieve orderly connections under the guidance of operation strands (Fig. 1c and Supplementary Figs. 4–6). Moreover, the flexibility of memory allocation extended beyond the node linkage from the same type of DON nodes, enabling allocation across different node types. The multiple-node linkage was extended to interconnect diverse types of nodes through serial operations, enabling concurrent processing. This approach could provide the possibility of storing multiple types of information (Fig. 1d and Supplementary Fig. 7).

Definition of data domain in DONLDS system
In this study, we conceptualized and crafted three DON nodes with the purpose of facilitating high-efficiency data operation. In devising our data storage scheme, we focused on optimizing the layout of the data domains. Leveraging the addressability of DON nodes in which staple strands have their own position, we were able to precisely utilize the central part of DON nodes as data domains. To denote the binary ‘1’ on the surface of the DON nodes, we implemented connections at SA linked domains (red dots), coupling streptavidin (SA) with biotin-modified data strands, only unlabeled biotin staples located at the SA linked domains are defined as code ‘0’. Because the size of SA is ~6 nm41, we adopted a minimum spacing of 20 nm between adjacent SA connection domains, thus effectively preventing neighboring effects and minimizing potential cross-interference (Fig. 2a).

The encoding process started with mixing the scaffold and staple strands together within a reaction system to induce their spontaneous self-assembly through annealing from 95 °C to 25 °C. The data writing process was achieved by covalently coupling SA-decorated data strands, thus enabling precise data placement on the DON nodes. Ultimately, AFM images confirm site-specific conjugation of SA to biotin-modified domains (Fig. 2b and Supplementary Fig. 8). To comprehensively evaluate the performance of these three distinct types of DON nodes, we conducted an in-depth comparative analysis of their size, capacity, and density. The results revealed that three types of DON nodes exhibited similar storage potential (Fig. 2c and Supplementary Tables 2–3). Specifically, each RDON node boasts an area of approximately 5400 nm2, which was capable of 12 bits of binary data. CDON and TDON nodes possess areas of around 4500 nm2 and 5072 nm2, respectively, each of which could store 8 bits of binary data. After calculating the storage density of these DONs, we define the maximum number of bits storable per cubic centimeter. The calculations indicated that the RDON boasts the highest storage density at 222.22 Gbit/cm2, followed by the CDON at 177.76 Gbit/cm2, with the TDON at 157.78 Gbit/cm2.

Establishment of English alphabet information storage by TDON nodes
To demonstrate the programmability of the DON nodes, we employed TDON for encoding English alphabets and pointers. Each TDON node was equipped with a data domain to encode in a clockwise spatial arrangement and the pointer domain to install pointer strands (Fig. 3a). Then, we developed a set of 8-bit binary codes for the 26 English letters. To ensure unambiguous spatial orientation, we used a fixed 3-bit orientation code (‘010’) and a streptavidin (SA) marker on the inner edge of side “a” to break rotational symmetry. This combination eliminates ambiguities from origami flipping and rotational misalignment, followed by a 5-bit alphabet coding set for letter differentiation. Take the English alphabet ‘A’ for example, the whole process would include four steps: inputting 8-bit binary sequence ‘01000010’ to the TDON node-based encoding system, reading the nodes by AFM, outputting the nodes into a binary sequence, and converting into ‘A’ (Fig. 3b). Following the rules, we input the corresponding binary data and created 26 distinct TDON nodes, which were read precisely by AFM. The experimental data indicated that SA could effectively dock with the predetermined storage domains, ensuring information storage accuracies of 91.17±0.86% to 95.64±2.05% for TDON nodes (Fig. 3c and Supplementary Figs. 9–11).

After the achievement of TDON-based storage nodes which emerged as the fundamental building block of the linked list data structure, we investigated the ability of the instructions to execute commands. The phrase ‘HELLO WORLD’ was demonstrated and decomposed into five English alphabet pairs independently, namely ‘HE’, ‘L1L2’, ‘OW’, ‘O2R’, and ‘L3D’. After anchoring five sets of DNA strands with specially designed DNA sequences as pointers onto the TDON nodes respectively, the instruction of linkage could be executed by introducing operation strands which generated 5 dimeric TDON nodes with an accuracy of 90.73±1.36% to 92.07±1.78% (Fig. 3d and Supplementary Fig. 12). Additionally, to verify the specificity between operation strands and pointer strands, we conducted instructions by co-incubating all ten monomer storage nodes with their corresponding operation strands in a single reaction system. The results showed that these ten nodes were able to connect precisely according to the predetermined connection objectives, resulting in the formation of five groups of dimeric nodes. Excluding the unpaired single nodes, the frequencies of the dimer nodes within the reaction system were 19.87±0.35% (HE), 19.43±0.46% (L1L2), 18.62±0.31% (OW), 19.25±0.32% (O2R), and 18.99±0.77% (L3D), respectively (Fig. 3e and Supplementary Fig. 13).

Construction of digital information storage based on CDON nodes
At the left and right sides of each CDON node, we meticulously designed six pointer strands with unique DNA sequences to facilitate the pairing of operation strands, thereby ensuring the stability and specificity of inter-node connections. To ascertain the reversibility and stability of information interconnectivity between CDON nodes, we conducted multiple rounds of connection and disconnection experiments on the data nodes. In the initial stage (stage 0), the CDON nodes remained mutually independent. After the introduction of operation strands to execute linkage instruction, the CDON nodes combined together to form dimers in stage 1. Here, the operation strands not only connected two CDON nodes, but had the toehold part for disconnection. Hence, the operation strands to execute disconnection instruction could result in two independent CDON nodes via toehold-mediated strand displacement, which is a fundamental mechanism in DNA nanotechnology where transient binding at short single-stranded “toehold” regions initiates branch migration to displace hybridized strands (stage 2). Of course, with the re-introduction of operation strands, the CDON nodes reconstituted the dimeric structures (stage 3, Fig. 4a). The statistical analysis of the average accuracy rates from stage 0 to stage 3 were 79.87% (connection) and 95.34% (disconnection) (Supplementary Fig. 14).

We also employed CDON nodes for digital information storage. The unique loop structure positioned on the right side of the cross-shaped storage nodes acted as a vital orientation reference, which could unambiguously determine the spatial orientation and configuration of the complete storage node. We selected four dedicated coding domains (positions 1-4 in Supplementary Fig. 15) within CDON nodes to implement 4-bit binary encoding for digital information storage. The AFM images vividly illustrated the ten CDON nodes for digital information storage, The data retention accuracy of CDONs ranged from 91.17±1.64% to 95.94±1.04% across three independent experiments (Fig. 4b and Supplementary Fig. 16).

To show the application of these CDON nodes, we constructed a linked memory to represent geographical coordinates which were capable of pinpointing precise locations on Earth and providing functionalities such as navigation, mapping services, and positioning. Because geographical coordinates usually contain latitude and longitude data, we used header nodes to show the latitude and longitude and data nodes to display the data (Fig. 4c). Within the CDON header node, the blue circle denoted the header node’s positioning point, while the gray circles were allocated for the storage of urban latitude and longitude. In addition, we established four binary positions within the header node: green for northern latitude, gray for southern latitude, red for western longitude, and orange for eastern longitude. For the data nodes, each was capable of storing 8 bits of binary information, which were converted into 2-digit decimal numerical data according to the encoding rules. In light of the extensive range and specific precision requirements for data denoted in degrees, it was customary to allocate one or two nodes for its retention. The storage demanded for such data spans from 0 to 12 bits of binary information, allowing for an nimble adaptation to the varying scales of data storage needs. By contrast, data annotated in minutes was more concise, requiring merely a single node to encapsulate, with its storage space confined to within 0 to 8 bits of binary information. This design ingeniously enhanced the efficiency of storage space while ensuring the high fidelity of data representation. Then, we assigned 7-bit binary codes and linked five or six CDONs for four cities (New York, Beijing, Brasilia, and Sydney), each representing a different global direction for storage (Fig. 4d). For example, a five-node structure was utilized to store the geographical coordinates of New York: 40°43’N, 74°00’W, in which the decimal latitude and longitude information (40°43’, 74°00’) was translated into binary data (01001100010000110111010011001100) and stored within the CDON nodes. The AFM images demonstrated the storage of the geographical coordinates for four cities (Fig. 4e and Supplementary Figs. 17–20).

Encoding Chinese characters information by RDON nodes
Chinese characters, which own a large amount of characters and abundant meanings, are usually encoded by 16 bits of binary numbers in the computer. To store Chinese characters efficiently and accurately, we established a 16-bit binary storage scheme according to GB2312, in which each Chinese character was represented by 4 Arabic numerals. We listed some of the Chinese characters with their zone-bit codes (Fig. 5c). Because of the larger storage space required for Chinese characters, two RDON nodes as a unit were utilized for one Chinese character instead of a single RDON node. Considering the symmetry of RDON nodes and the order of Chinese characters, the RDON unit was divided meticulously into three domains, including the index domain, orientation domain, and Chinese character domain. The index domain was encoded by four red marker circles to establish the reading order of the characters, ensuring the accuracy of information retrieval. The orientation domain was indicated by three blue marker circles, which could ensure the information in the correct direction. Analogous to the scaffold loop in CDON, the RDON dimer employs its blue orientation domain to break structural symmetry (Fig. 5a). The orientation domain cooperates with the scaffold loop to enforce uniform node orientation during substrate adsorption, eliminating data readout ambiguity caused by structural flipping. The Chinese character domain was responsible for storing the binary encoding information of Chinese characters with 16 gray marker circles in four rows, which were read from left to right and from up to down (Fig. 5a). Taking the Chinese character ‘HOU’ for example, it was firstly searched in GB2312 to obtain its zone-bit code 2681. Then, the number was encoded into a 16-bit binary RDON unit via a coding mapping procedure. Finally, the generated RDON unit could be read and decoded into ‘HOU’ (Fig. 5b). According to these encoding standards, eight Chinese characters, which mean noble morality, strong mind, seek the truth and practice earnestly, were encoded into eight independent RDON nodes and validated by AFM images and their height analysis (Fig. 5c and Supplementary Figs. 21–28).

Beyond monomeric RDON nodes, we leveraged RDON’s modular expandability to augment storage capacity specifically within the Chinese character domain (excluding the index and orientation domains). We demonstrated storage of the traditional Chinese maxim ‘DAOKEDAO FEICHANGDAO’ from the Tao Te Ching using an RDON tetramer, achieving 48-bit capacity at 222.22 Gbit/cm2 density. This resolves the long-text storage bottleneck, and the modular architecture underpins future chain or grid-based large-scale DONLDS system (Fig. 5d, Supplementary Figs. 29–30).

The linked data storage of different types of information
The distinguished feature of DONLDS system lies in its capacity as a storage medium to facilitate precise control over the connection and disconnection between DON nodes, which greatly facilitates efficient insertion and removal of data elements. In this process, there is no need for extensive rearrangement or reconfiguration of the entire structure, thereby maintaining the consistency and integrity of the data structure. The workflow executed by the DONLDS system illustrated the processes of data insertion and deletion. (Fig. 6a–b). Then we turned to delineate the intricate process of data insertion and deletion by RDON nodes. Prior to data manipulation, a linked list was constructed by the linkage of RDON nodes 1, 2 and 4 with linking strands. When executing the insertion operation between nodes 2 and 4, the detachment strands were introduced and nucleated at the toehold domains to initiate the strand-displacement reactions, which generated the disconnection of nodes 2 (P, denoting ‘previous’ node) and 4. Then, two new linking strands were added to form the linkage of the pointer of node 3 (S, denoting ‘subsequent’ node) with that of nodes 2 (P) and 4, thereby facilitating the completion of the data insertion process. The deletion operation aimed to remove node 2 (P) from a list consisting of four nodes. This was achieved by simply disconnecting node 2 (P) from its adjacent nodes and establishing a new linkage between nodes 1 and 3. Here, the operation of pointer replacement was achieved through a sophisticated DNA strand displacement, which ensured the high precision, reliability, and stability of the data list editing process at the molecular scale. This strand displacement mechanism leverages the properties and complementarity of DNA molecules, accomplishing precise adjustment of pointers between nodes through a process of carefully designed sequence matching and strand exchange (Fig. 6c and Supplementary Fig. 31).

To further underscore the scalability of DON nodes in data storage, we crafted an interconnection mechanism among variously shaped DONs. These strategic linkages not only augmented the synergy between nodes but also markedly enhanced flexibility and capacity in the overall storage system. As depicted in Fig. 6a, our storage nodes consist of three TDON, four RDON, and two CDON nodes, each boasting a unique base-pairing scheme and a complex folding architecture. Initially, we constructed a bidirectional linked list comprising nine nodes, and through the execution of deletion and insertion operations, the initial list 1 was transformed into list 2 (Fig. 6d).

The paramount advantage of the DONLDS technology lies in its dynamic memory space allocation capabilities. Following data encoding and storage, we sequentially linked each structure with detachable operation strands. To ensure the stability and reliability of data transmission, we designed six to eight sets of distinct pointer strands between different-shaped DONs, each of which was a unique sequence for high-specificity recognition with the operation strands. This allowed each DON to interlock and complement one another like precision gears, forming a highly modular and expandable linked list. We encoded the English letters ‘D’, ‘N’, and ‘A’ by TDON nodes, Chinese characters ‘LUO XUAN’ for ‘HELIX’ by RDON nodes, and the CDON nodes for the historically significant digits ‘1953’, signifying the year of the discovery of the DNA double helix (Fig. 6e and Supplementary 32–34). In constructing our DONs linked list, we specifically designated the triangular DON node as the head node. To distinctly mark this node, A SA connection domain was embedded within the edge “a” of TDON as an identifying feature of the head node. Subsequently, we connected the RDON and CDON nodes to the head node by the predetermined connection logic. AFM images validated the interconnection of the nine distinct storage nodes. By analyzing the height variations presented in the images and converting them into corresponding binary data, we stored the complete multi-type textual information ‘DNA-HELIX-1953’ (Fig. 6e and Supplementary Fig. 37). This experimental outcome robustly demonstrates the exceptional capabilities of the DONLDS technology in the splicing of multi-type storage nodes, proving its ability to seamlessly integrate data between nodes of varying shapes and types, while maintaining data storage accuracy and stability with high efficiency.

Subsequently, we undertook the transition from linked list 1 to linked list 2. In the preliminary stage, we disconnected the data linkage between the TDON node T3 and the RDON node R1. This was achieved by introducing inter-node unlocked strands, deftly substituting the operation strands within the nodes, thereby facilitating the operation of data deletion. Thereafter, within the newly generated RDON nodes, we encoded and stored the Chinese character ‘storage’, while the CDON nodes recorded the number ‘1988’, signifying the year the concept of DNA storage was first proposed (Fig. 6f and Supplementary Figs. 35–36). Ultimately, by introducing the operation strands of nodes T3 and R5, as well as R8 and C3, and performing base-complementary pairing with their pointer strands, the insertion operation of the ‘STORAGE-1988’ linked list was executed. The AFM images depicted the storage of the ‘DNA-STORAGE-1988’ sequence, with the detailed imagery showcasing the integrity of the data (Fig. 6g and Supplementary Fig. 38).

To minimize error accumulation, we employed a composite reading strategy involving cross-verification of multiple nine-node units. Decoding thresholds were established as follows: a signal connection (SA) exceeding 80% was interpreted as ‘1’, a connection below 20% as ‘0’, and connections between 20% and 80% were considered invalid bits. Analysis of 24 randomly selected samples (totaling 1728 bits) revealed a 100% recovery rate when compared bitwise with the pre-defined ‘DNA-STORAGE-1988’ sequence (Supplementary Figs. 38–39). This experimental result further validated the potential application value of DNA nanotechnology-based data processing systems in the realm of information storage and manipulation. To accurately predict the storage success rate for larger-scale data, we use a refined computational model. This model is described in detail in the supplementary methods section, which includes parameterized mathematical formulas that systematically calculate the data storage success rate under corresponding conditions by taking the raw bit error rate as an input variable (Supplementary Table 4 and Fig. 40).

Methods
Materials
All chemicals were obtained from Sigma (USA). All short strands were purchased from Sangon (ULTRAPAGE purification, Shanghai, China). Biotin-modified oligonucleotides were supplied by Sangon and purified by high-performance liquid chromatography (HPLC). M13mp18 DNA was purchased from Bioruler (cat. no. B3003, Jiangsu, China), The sample was stored in 500 μL of water at a concentration of 100 nM. The streptavidin powder was obtained from Sigma (cat. no. S4762, USA). All solutions were prepared with Milli-Q water (resistivity = 18.2 MΩ cm).

Synthesis of DON nodes
The single-stranded DNA of the M13mp18 virus was selected as the scaffold strand. The scaffold strands (100 nM) and staple strands (100 μM) were mixed at a 1:10 molar ratio in 1× TAE/Mg2+ buffer solution in the experiment. The components of the buffer include 40 mM Tris (to maintain pH, Sigma, cat. no. 252859), 20 mM acetic acid (Sigma, cat. no. 338826), 12.5 mM magnesium acetate (Sigma, cat. no. 228648), and 2 mM EDTA (Sigma, cat. no. 798681). The mixed DNA solution was then transferred to a PCR instrument (Thermo Fisher Veriti Fast, cat. no. 4375305) for precise temperature control. Initially, the solution was heated to 95 °C for 5 min to denature the single-stranded DNA and ensure homogeneity of the mixture. The temperature was then gradually decreased to 10 °C at a rate of 1 °C per minute, facilitating a slow annealing process that promotes the formation of stable and precise hybrid structures between the staple and scaffold strands.

Purification of DON nodes
Excess DNA staple strands were purified using ultracentrifugal filters 100K ultrafiltration tubes (Merck millipore, cat. no. UFC5100BK). The sample solution was combined with 400 μL of 1× TAE/Mg2+ solution and transferred to the ultrafiltration tube. It was then centrifuged at 25 °C and 3000 g for 10 min to eliminate residual liquid from the tube’s base. Subsequently, 400 μL of 1× TAE/Mg2+ solution was added to the tube for centrifugation, and this process was repeated three times. Following the repetitions, the ultrafiltration tube was inverted, placed in a new ultrafiltration tube holder, and centrifuged at 1000 g for 10 min to achieve purified DON. Finally, UV quantification was performed on the purified monomeric DON to determine the concentration of each DON.

Synthesis of data strands
Streptavidin powder was dissolved in 1× PBS/Mg2+ buffer to prepare a 1 mg/mL stock solution. This stock was then diluted in the same buffer to a final working concentration of 5 μM for the experiments. The components of the buffer include 10 mM sodium dihydrogen phosphate (Sigma, cat. no. 71500), 2 mM disodium hydrogen phosphate (Sigma, cat. no. 71643), 137 mM sodium chloride (Sigma, cat. no. S7653), 2.7 mM potassium chloride (Sigma, cat. no. P3911), and 12.5 mM magnesium acetate (Sigma, cat. no. 228648). The 3’ end of staple strands was modified with biotin to enable its connection to streptavidin (SA). The biotinylated staple strands (100 μM), following modification, was then mixed with SA (5 μM) in a precise 1:1 molar ratio and thoroughly agitated to ensure uniformity of the mixture. After homogenization, the solution was placed on a shaker and incubated for 2 h at a constant temperature of 37 °C to facilitate effective binding between the biotinylated staple strands and SA. Excess SA were purified using ultra centrifugal filters 50K ultrafiltration tubes (Merck Millipore, cat. no. UFC5050BK).

The data writing process of DON nodes
The purified DON nodes (2.5 nM) were mixed with data strands (100 μM) in a 1:10 molar ratio, and the mixed DNA solution was transferred to a thermal cycler (Thermo Fisher Veriti Fast, cat. no. 4375305) for an accurate annealing procedure. Firstly, the solution was heated to 50 °C, and then gradually decreased to 25 °C at a rate of 1 °C per minute. This completed the data writing process.

The serial operation of DON nodes
The serial operation of DON nodes is achieved through base pairing between the operation strands and their edge pointer strands. Mix DON nodes at a molar ratio of 1:1 and then add equal concentrations of operation strands to the solution system. Finally, place in a thermal cycler (Thermo Fisher Veriti Fast, cat. no. 4375305) for the annealing process as follows: heat to 45 °C at a rate of 1 °C per second, then cool from 45 °C to 25 °C in 2 h (decrease by 0.33 °C per minute).

Reading the information on DON nodes
The DON nodes were analyzed using a Microscope MultiMode VIII atomic force microscope (Bruker, USA). Initially, 5–10 μL of the DON was deposited drop by drop onto the mica surface for 3 min. Afterward, the mica was rinsed with 400 μL ultra-pure water, and completely dried using a washing ear ball. The mica sheet was then positioned on the AFM stage for imaging in Tapping mode in air, with parameter adjustments optimized for data capture. The results were analyzed by the Nanoscope analysis (Bruker).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Excellent work! This manuscript reports a strategy for linked data storage based on DNA origami nanostructures. Large-scale, long-term data storage is an urgent challenge to current society. To solve this problem, DNA has been very actively explored as a media for such data storage. Based on previous work, but with great a breakthrough, this manuscript develops a methodology to dynamically link data together based on DNA self-assembly for quickly writing, retrieve, and editing data. Different from direct sequence-coding in most of the DNA-based information storage, this work is based on nanostructures, which could be from different set of DNA sequences (for the same nanostructures). Thus, it is more dynamic and flexible. Among many others, one impressive aspect is the achievement of very high data density in storage. Great idea and very concrete experimental support. This referee strongly recommends for publication.\nMinor comments:\nFig. 1c, the symbol for used node is the almost the same as the symbol for TDON node. That is probably not what the authors intend to show. Please pick more distinct colors.\nFig. 2a, a CDON seems to have a capacity to have another four data domains at the four corners of the central overlapping area. It is also possible to have more data domains for TDON. That would boost the data density quite a lot. Could the authors comment on why use the current choices.\nThe arrangement of the data domains is an important factor for this study, it would be helpful to draw the DNA nanostructure schemes with the correct size ratio for different dimensions. Currently, they are not. For example, the scheme and the AFM image of the TDON differ quite a lot.\nA related issue, it is understandable to use the particular three DON shapes because they are well characterized and convenient to use. But those structures might not be the best for the current purpose. It is worth including a brief discussion about the idea DON shapes for linked data storage.", "reviewer_2": "The manuscript deals with a popular topic – data storage in DNA. There are quite a few challenges in the field – such as data retrieval and accuracy. The authors developed a linked data storage system using DNA origami nanostructures (DONs) as storage media (so information is NOT stored in the bases of the DNA). The general idea to use DNA origami for information encoding is not new, and a faster readout with fluorescence has been demonstrated (https://pubs.acs.org/doi/full/10.1021/acscentsci.4c01557) although information encoding and readout with AFM, as used here, has also been demonstrated (https://www.cell.com/biophysj/fulltext/S0006-3495(22)00734-2).\nWhat I find novel and quite nice (although quite limited practically speaking) is the data re-writing idea which lifts the technology beyond “cold” archiving, based on the commonly used strand displacement strategy. However, I have some comments that should be addressed before publication in any form – importantly the lack of information on statistics.\n1) From the applications perspective, I see several severe limitations – the reliance on comparably slow AFM for reading, the high cost and scalability issues, and the fact that individual nodes only store 8-12 bits – leading to a super high error rate for even relatively small amounts of data. This should be at least discussed openly.\n2) Do the authors see strategies for faster readout? Have they thought about fluorescence?\n3) Can they do an estimation calculation on how the fidelity of the information storage scales with the amount of information stored based on the data they already have?\n4) From the text it is unclear if the authors actually made the designs themselves from scratch or if they were adapted from previous designs (in that case the origin should explicitly be cited).\n5) Statistical information is largely missing. The author state yields of the correct assemblies, but how were they determined? How many independent experiments where conducted (no error bars are shown)\n6) If the receiver does not know what information is encoded, how do you distinguish between a bad AFM image or a dirty tip, where not every streptavidin can be seen and an actual change in information? Do they use automated analysis for readout? This would help avoid bias.", "reviewer_3": "This article by Zhang et al. describes how DNA origami nanostructures can be used for \"linked data storage\". It is not the first paper of its kind where DNA origami is used for some way of computing or data storage but it is a field that has become very active after 20 years of being ignored by many. Before acceptance of this manuscript, we recommend major revisions as outlined below.\nMain concerns:\n1. The biggest concern I see is if the orientation of the nodes can really be reliably determined for correct read out of the bit values. In general, the DONs can land in different orientations and according to Fig.2c for TDONs also with either of the two surfaces oriented towards the substrate and this leads to read out problems, when some of the bits in a node are set to 0.\nFig. 3b implies single TDONs can be identified deciphered into the letters they are coding for, but in Fig 3c, there are multiple ambiguous codings, when taking into account rotations and filipping of the DONs: If you flip the DON for J, if matches the one for D, despite the \"symmetry breaking\" 010 sequence, the same goes for M and Y (AFM images for M and Y are the same). J and Q are connected through a 120 deg rotation, also Y and K. I do understand that the symmetry is additionally broken by the pointer strand domains, so in most cases of longer words, the readout wouldn't be ambiguous, but it is not clear to me, that this is true for every combination of letters, especially if we consider only two letter syllables. I also do not understand how the direction of reading of the nodes is determined in the case of symmetrical TDONs. For instance, the word MH, can only be read in this direction. However, if it is flipped to face the substrate with the top side, the letters become YH. What is more, it can be read also in the opposite direction, yielding the word MK. This might not be an issue for longer words, but it should still be discussed/explained.\nFor the CDONs the authors explain that the presence of a scaffold loop helps to break the symmetry and enables unambiguous read-out. This seems also to be the case for RDON dimers, but it is not clearly explained in the text. If so, this would be enough in combination with the blue \"orientation domain\" from Fig. 5 to mark the proper orientation of the RDONs, but it does not help with orienting the RDON tetramers, which do not have orientation domains and could be flipped to their top side to face the substrate.\nOn a related note, in the paragraph starting with line 313, the authors use tetramers of RDONs to encode longer phrases with chinese characters. Why is there no need for an \"orientation domain\" as in the case of RDON dimers from the previous paragraph? This should be clarified in the text.\n2. There is a fundamental problem if one desires to encode data storage by linking DNA origami structures: Finding reliable and practically orthogonal sequences. On paper two different sequences look great (e.g. GTTGTTTT vs. TTTTTTTT) , but such sequences will easily bind to any sequence containing many As (like AAAAAA). Especially if there are plenty of such sequences with slight complementarity next to each other on an origami they bind like velcro. In other words: just being orthogonal sequences on paper does not exclude them binding to each other at room temperature. This requires discussion.\nAlong this line: To use the DONLDS seriously as data storage system, a base of pointer and operation staples should be made. It would be beneficial to discuss how the needed number of strands scales with the number of bits the system is able to store.\n3. Also in this context: The design scheme of the pointer and operation strands presented in Fig. 1b is cryptic. Neither the main text nor the figure caption explain how these non binary numbers (and letters) correlate to the 16nt DNA sequences. Is there any logic (does a number at a certain position denote a specific nucleotide?) or how are the sequences chosen? Give examples.\n4. Why are only TDON dimers used to encode two letters at a time instead of the whole \"Helloworld\" phrase in a single sequence of nodes?\n5. The authors claim a high information density, which is true locally for each DON, but in reality each object, or data string is produced in many copies. The effect of this redundancy on the information density should be be taken into account in discussion.\n6. Data reliability and streptavidin-encoding of 0 and 1: how to deal with errors? DNA origami researchers know that often staples or extensions are missing in any given DNA origami, which is also reflected in \"information storage accuracies of 92.31%~96.61% for TDONS\". I expect those to be worse for RDONS, e.g. most RDONs in Fig. 2C are not completely covered.\nMinor comments:\nIt could be good to shortly define hot and cold storage. One has a rough idea about it, but the broad readership of Nature Commun. could appreciate this.\nline 42: With the development of techniques ... - what kind of techniques?\nlines 86-87: The way it is presented, it is not clear what is meant with \"DNA helix ...\" and \"DNA storage ...\". Maybe: \"...ability of a linked list based on DONs to store the string 'DNA helix 1952' and edit it with data deletions and insertions for ...\"\nline 112/Supl. Fig. 2 - it is not clear how these pointers work - what are the physical positions of the DONs in a memory unit in Fig.S2 supposed to represent? How can one tell apart the different nodes of the same type? \"N\" pointer is not defined\nline 140: \"... while the non biotin labeled staples were defined as the code '0'\" - If I understand correctly (e.g. in the case of RDON) only 12 out of the 216 staples are potentially modified with biotin, so not every staple which is not biotin labeled serves as a 0 binary value. Also in the caption (and in the main text) it could be better explained that the red dots in Fig.2a are places where SA is potentially attached, defining either a 0 or 1 bit.\nline 148: \"...each DON node was perfectly aligned with SA ...\" What do you mean by \"perfectly aligned\"? Perhaps \"modified\" or \"coupled\" or similar?\nlines 200-201: it would probably be beneficial to explicitly state that this \"simultaneous conduction of instructions\" was done by mixing all ten monomer storage nodes with all the operation strands - this might not be obvious to a person not from the DNA nanotechnology field.\nIn Lines 204-206: I would avoid calling these ~20% values \"accuracies\", if I understand correctly, these are frequencies. I assume in this experiment the expected frequencies are 20% for each of the dimers? If so, the accuracy of dimer formation for each dimer is close to 100%, not 20%.\nline 232: toeholds & toehold-mediated strand displacement is introduced without any explanation or background\nFig. S14 shows 8 positions for the \"bits\" on the CDON, but only 4 are used to encode the arabic numerals and it its not clear which 4.\nIn lines 350-351 the authors introduce P and S as labels for different nodes without any explanation of the meaning.\nBecause of abundance of other letters in Fig. 6 with different meanings (N & Y for no and yes, T, R & C for different types of nodes and the encoded english letters) this is confusing, so please explain the meaning and perhaps consider a different label for the deleted and inserted nodes.\nIn Fig 6a, it would be clearer to the reader if \"no\" and \"yes\" were used instead of \"n\" and \"y\"\nline 384: it is not clear what is meant by \"a specialized SA connection domain\" that serves as the identifying characteristic of the head node\nline 432: \"We demonstrated ... 8 Chinese characters ...\" While it is true that the authors demonstrated only a limited selection of chinese characters, this system could in principle encode any chinese character. I think the authors should state this clearly so that this is not taken as a limitation of the DONLDS.\nThe manuscript would benefit from proof-reading. Most of the text is written in past tense and passive voice, which can be confusing, especially with figure captions, e.g. Fig 3b: \"A flowchart for the writing and reading process of English letters was illustrated. The figure depicted the English alphabet alongside its corresponding binary code table and provided a stepwise depiction of the encoding procedure for the letter ‘A’ within the TDON node.\"\nSome examples of other language issues:\nline 24: ... different shaped DNA origami ...\nline 31: ... nanostructure-enabled ...\nline 43: ... which IS characterised ...\nline 56: ... different TO sequential storage ...\nline 58 ... obviate .. is unnecesarily uncommon word\nline 64: … the DNA PAINT technology\nline 72: …developed A DNA origami nanostructure-enabled\nlines 96-97: Benefitting to the programmability ...\"\nline 146-147: \"... covalently coupling data strands decorated SA, ...\"\nline 156: \" After calculated the storage density ...\"\nline 162: … The DON constituted a sophisticated design schema for data storage -> DON-based design scheme for data storage (if it is sophisticated or not is a question of taste)\nline 164: … collaboratively forging a robust DNA nanostructure -> meaning of forging is mainly in the direction of \"counterfeiting\", \"pretending to be\"\nline 178: … encode the clock wisely?\nline 180: \"... English alphabets.\" - should be \"letters\"\nlines 192-193: \"... we turned to investigate the ability of the instructions to executive commands.\"\n296: character instead of INDIVIDUAL RDON nodes\nline 296: probably should say: \"...instead of A SINGLE RDON node.\"\nline 313: \"Other from ...\"\nline 344: \"... were illustrated the workflow executed ...\"", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Thank you for your evaluation and constructive suggestions on our manuscript. We are grateful for the opportunity to revise our work and address the concerns raised. Below, we provide a detailed point-by-point response to each commenter’s comments. All updates in the revised manuscript are highlighted in yellow characters.\nREVIEWER COMMENTS\nReviewer #1\nExcellent work! This manuscript reports a strategy for linked data storage based on\nDNA origami nanostructures. Large-scale, long-term data storage is an urgent challenge\nto current society. To solve this problem, DNA has been very actively explored as a\nmedia for such data storage. Based on previous work, but with great a breakthrough,\nthis manuscript develops a methodology to dynamically link data together based on\nDNA self-assembly for quickly writing, retrieve, and editing data. Different from direct\nsequence-coding in most of the DNA-based information storage, this work is based on\nnanostructures, which could be from different set of DNA sequences (for the same\nnanostructures). Thus, it is more dynamic and flexible. Among many others, one\nimpressive aspect is the achievement of very high data density in storage. Great idea\nand very concrete experimental support. This referee strongly recommends for\npublication.\nResponse: We sincerely thank Reviewer #1 for the enthusiastic endorsement of our\nwork and the constructive suggestions. We deeply appreciate their recognition of the\ninnovation and technical rigor of the DONLDS system, particularly its dynamic linkage\nmechanism and high-density storage capacity. Below, we have addressed the reviewer’s\ncomments in detail and outline our revisions to address these points.\nComment 1: Fig. 1c, the symbol for used node is the almost the same as the symbol\nfor TDON node. That is probably not what the authors intend to show. Please pick more\ndistinct colors.\nResponse: We sincerely appreciate the reviewer’s valuable feedback regarding Figure\n1c. The circular symbols representing used nodes have been modified to a high-contrast\nred fill (#FB7979), significantly enhancing visual distinction between node types as\nsuggested.\nFig. 1 | c, A Schematic diagram of memory unit connections based on three shapes of\nDON. The tetramer linked DONs were depicted in AFM images.\nThe images have been replaced in Figure 1c of the revised manuscript. (Page 5, line\n132)\nComment 2: Fig. 2a, a CDON seems to have a capacity to have another four data\ndomains at the four corners of the central overlapping area. It is also possible to have\nmore data domains for TDON. That would boost the data density quite a lot. Could the\nauthors comment on why use the current choices.\nResponse: We appreciate the reviewer’s insightful comment regarding the potential for\nincreasing data density by adding more data domains to CDON and TDON nodes.\nIn devising our data storage scheme, we focused on optimizing the layout of the data\ndomains, leveraging the addressability of DON nodes in which staple strands have their\nown position. We precisely utilized the central part of DON nodes as data domains and\nimplemented connections at specified locations, coupling streptavidin (SA) with biotin-\nmodified data strands to denote the binary ‘1’, while non-biotin labeled staples were\ndefined as the code ‘0’. Given the size of SA (~6 nm), we adopted a minimum spacing\nof 20 nm (vertical spacing: 20 nm, horizontal spacing: 21.8 nm) between adjacent SA\nlinked domains to prevent neighboring effects and minimize potential cross-\ninterference. To enhance clarity in understanding our design, we have relabeled Fig. 2a\nand Supplementary Fig. 8a with the theoretical values between SA-linked domains.\n(NEW Fig. 2a and Supplementary Fig. 8a)\nWhile it is theoretically possible to add more data domains at the corners of CDON\nor to TDON, we chose the current configurations to balance data density with data\nreliability. The 20 nm spacing requirement, dictated by the size of SA and the need to\nminimize interference, limited the number and placement of data domains on the DON\nnodes. Adding more domains without sufficient spacing could compromise the\naccuracy of data reading and writing, negating the benefits of increased density. Future\nstudies could explore methods to reduce SA size or mitigate interference, potentially\nallowing for higher data density.\nSupplementary Fig. 8 | a, The structural diagrams and AFM of the scaffold and staple\nstrands of RDON, CDON, and TDON. The minimum distance between adjacent SA\nconnection domains is marked in the figure.\nThe images have been replaced in Figure 8a of the revised Supplementary. (Page 12)\nComment 3: The arrangement of the data domains is an important factor for this study,\nit would be helpful to draw the DNA nanostructure schemes with the correct size ratio\nfor different dimensions. Currently, they are not. For example, the scheme and the AFM\nimage of the TDON differ quite a lot.\nResponse: We appreciate the reviewer’s insightful comment regarding the accuracy of\nthe size ratios in our DNA nanostructure schemes. We acknowledge that there are\ndiscrepancies between the schematic representations and the AFM images, particularly\nfor the TDON. In the revised manuscript, we have redrawn the DNA nanostructure\nschemes with more accurate size ratios (NEW Fig. 2a–b), taking into account the\ndimensions observed in the AFM images. We also verified and modified the scales\nrelated to DNA origami in Figures 1 to 6. This provides a more realistic representation\nof the structural arrangements.\nFig. 2 | DON-based design scheme for data storage. a, DONs were delineated by a\nblack linear framework signifying its scaffold strands, complemented by blue filigrees\nthat represent the staple strands, collaboratively assembling a robust DNA\nnanostructure. SA conjugation was marked by a bold red dot. b, The synthesis and data\nencoding process of DON nodes involves the utilization of M13 single-stranded DNA\nextracted from Escherichia coli as the scaffold, the data strands along with SA are\naffixed to these nanostructures, thereby accomplishing the encoding process. The AFM\nimage depicting all domains of the three DONs, each interfaced with SA for the storage\nof information. Scale bar: 50 nm.\nThe images have been replaced in Figure 2a-b of the revised manuscript. (Page 7, Line\n173)\nComment 4: A related issue, it is understandable to use the particular three DON shapes\nbecause they are well characterized and convenient to use. But those structures might\nnot be the best for the current purpose. It is worth including a brief discussion about the\nidea DON shapes for linked data storage.\nResponse: Response: We appreciate the reviewer’s comment regarding the choice of\nDON shapes and the potential for exploring alternative designs optimized for linked\ndata storage.\nWhile the triangular (TDON), rectangular (RDON), and cross-shaped (CDON)\nDONs employed in this study may not inherently represent the theoretical optimum for\nlinked data density or access efficiency, our primary objective with these shapes was to\nrobustly demonstrate the fundamental versatility and adaptability of our proposed\nDONLDS architecture across diverse, readily fabricable structures. we acknowledge\nthat these shapes may not be inherently optimal for linked data storage, and DON’s\nshape optimization is a crucial direction for future work.\nIn the revised manuscript (Page 21, Lines 498–504), we have included a brief\ndiscussion about the ideal DON shapes for this purpose: “While DONLDS currently\nutilizes TDONs, RDONs, and CDONs for ease of fabrication, achieving optimal linked-\ndata storage necessitates balancing multiple factors: pointer domain complexity, data\ncapacity/density, structural stability, addressability, and synthesis feasibility. For\ninstance, hexagonal DONs could offer greater pointer complexity, whereas circular\nDONs maximize data storage area but present challenges for placement precision and\nstructural rigidity. Future designs will systematically explore these shape-dependent\ntrade-offs.”\nReviewer #2:\nThe manuscript deals with a popular topic – data storage in DNA. There are quite a few\nchallenges in the field – such as data retrieval and accuracy. The authors developed a\nlinked data storage system using DNA origami nanostructures (DONs) as storage media\n(so information is NOT stored in the bases of the DNA). The general idea to use DNA\norigami for information encoding is not new, and a faster readout with fluorescence has\nbeen demonstrated (https://pubs.acs.org/doi/full/10.1021/acscentsci.4c01557) although\ninformation encoding and readout with AFM, as used here, has also been demonstrated\n(https://www.cell.com/biophysj/fulltext/S0006-3495(22)00734-2).\nWhat I find novel and quite nice (although quite limited practically speaking) is the data\nre-writing idea which lifts the technology beyond ‘cold’ archiving, based on the\ncommonly used strand displacement strategy. However, I have some comments that\nshould be addressed before publication in any form – importantly the lack of\ninformation on statistics.\nResponse: We appreciate the reviewer’s positive feedback, particularly their\nrecognition of the novelty in our data re-writing approach using strand displacement,\nwhich moved beyond traditional ‘cold’ archiving. We acknowledged the reviewer’s\nconcern regarding the lack of statistical information and addressed this in our revised\nmanuscript. We provided detailed information on assembly yields, including the\nmethods used for determination, the number of independent experiments conducted,\nand error bars where appropriate.\nComment 1: From the applications perspective, I see several severe limitations – the\nreliance on comparably slow AFM for reading, the high cost and scalability issues, and\nthe fact that individual nodes only store 8-12 bits – leading to a super high error rate for\neven relatively small amounts of data. This should be at least discussed openly.\nResponse: We sincerely appreciate the reviewer’s insightful critique regarding the\npractical limitations of our DONLDS system. We fully acknowledge these challenges\nand have expanded our discussion in the revised manuscript.\n1. AFM reading speed limitation\nWe acknowledge that traditional AFM faces scanning speed limitations. However,\nhigh-speed AFM (HS-AFM) has achieved revolutionary speed improvements in recent\nyears through hardware innovations and intelligent algorithms, as supported by\nreferences 54–57 in our manuscript: Degenhardt et al. integrated AFM topography with\n3D convolutional neural networks to resolve RNA conformational dynamics, enabling\na tenfold increase in classification speed for transient RNA folds (Ref. 54). Heath &\nScheuring pioneered label-free µs HS-AFM height spectroscopy for biomolecular\ndynamics (Ref. 55). Kanaoka et al. demonstrated real-time millisecond imaging of\nsingle SecYEG-SecA complexes during protein translocation (Ref. 56). Jiang et al.\nvisualized transporter ‘wanderlust kinetics’ (non-directional diffusion) via HS-AFM\n(Ref. 57).\nWe have expanded the relevant discussion sections of the Conclusions in revised\nmanuscript (Page 22, Lines 531–536): “Continued advancements in AFM techniques,\nsuch as the application of AI-AFM fusion to RNA dynamics, alongside techniques\nenabled by High-Speed Atomic Force Microscopy (HS-AFM) like label-free\nspectroscopy at microsecond resolution, millisecond-scale imaging of single-\ntranslocon complexes, and visualization of transporter diffusion kinetics, hold the\npotential to improve DON data read speeds by orders of magnitude.”\n2. Cost and scalability challenges\nRegarding cost and scalability, we acknowledge that large-scale DNA origami\nsynthesis is currently expensive. However, we emphasize that researchers are actively\npursuing breakthroughs in synthesis with emerging technologies such as enzymatic\nDNA synthesis and high-density microarray chips (Refs. 10, 42-43). These technologies\noffer the potential for faster base coupling, parallel processing, and reduced synthesis\ncosts. Furthermore, the coupling of DNA and semiconductor technologies, combined\nwith innovations in microfluidics, optics, and automated DNA synthesis equipment,\nholds considerable promise for driving down reagent and synthesis expenses (Refs. 44-\n46). We have made a detailed discussion and outlook on lines 471 to 488 of the paper.\n3. Low per-node capacity (8-12 bits) and error rates\nWe thank the reviewers for emphasizing these key considerations. For this purpose,\nwe have provided new experimental indicators and schemes to illustrate this issue.\n1) The storage accuracy of a single node is stable and controllable. The yield of\naccurate TDONs coding information ranges from 91.17 ± 0.86% to 95.64 ± 2.05%\n(New Figure 3c and supplementary Figures 9–11), and that of CDONs ranges from\n91.17 ± 1.64% to 95.94 ± 1.04% (New supplementary Figure 16). The accurate yield\nof TDONs coding information in dimer assembly ranged from 90.73 ± 1.36% to 92.07\n± 1.78% (New Figure 3d and supplementary Figure 12).\n2) To suppress error accumulation, we used a composite reading strategy cross\nvalidates signals from multiple nine-node units. Decoding thresholds were defined as:\nSA connection >80% = ‘1’, <20% = ‘0’, and 20%-80% = invalid bit (New\nSupplementary Figures 38–39). In 24 randomly selected samples (1728 bits total),\nbitwise comparison with the preset ‘DNA-STORAGE-1988’ sequence showed 99.99%\nrecovery rate.\nWe have clearly discussed these restrictions and supplemented relevant\nexplanations in the revised manuscript:\n“To minimize error accumulation, we employed a composite reading strategy\ninvolving cross-verification of multiple nine-node units. Decoding thresholds were\nestablished as follows: a signal connection (SA) exceeding 80% was interpreted as ‘1’,\na connection below 20% as ‘0’, and connections between 20% and 80% were\nconsidered invalid bits. Analysis of 24 randomly selected samples (totaling 1728 bits)\nrevealed a 99.99% recovery rate when compared bitwise with the pre-defined ‘DNA-\nSTORAGE-1988’ sequence (Supplementary Figures 38–39).” (Page 18, Lines 432–438)\n“To further mitigate error accumulation, we have developed a composite readout\nstrategy leveraging a polymeric architecture. This strategy achieves complete data\nrecovery by performing cross-validation on signals from multiple nodes. Thus,\nDONLDS is poised to play a significantly greater role in the field of information storage,\nparticularly in handling complex data structures and storing/modifying multi-type\ninformation.” (Page 22–23, Lines 539–544)\nData for review only: Review Figure 1: Data integration from supplementary figures\n9-11. The yield of single-node TDONs encoding English letters A-Z was 91.17 ± 0.86%\nto 95.64 ± 2.05%. Error bars represent SD, n = 3.\nSupplementary Figure 39 | Based on the analysis of multi-component DNA storage\ninformation (DNA-STORAGE-1988), the SA connection percentage of 24 independent\nsamples was statistically evaluated. Each sample contains 72 connection sites, totaling\n1728 sites. In the threshold settings, connection percentage above 80% are marked as\nbinary ‘1’, while those below 20% are marked as binary ‘0’. Source data are provided\nas a Source Data file.\nThe images have been replaced in Figure 39 of the revised Supplementary. (Page 43)\nComment 2: Do the authors see strategies for faster readout? Have they thought about\nfluorescence?\nResponse: We thank the reviewer for raising these critical points regarding readout\nefficiency. Faster readout is indeed essential for DONLDS system, we have discussed\nin the conclusion part in revised manuscript (Page 22, lines 531–536).\nHigh-Speed AFM (HS-AFM)1-4 technical path can improve the reading speed: HS-\nAFM has overcome the scanning speed limitations of traditional AFM. HS-AFM\nenables millisecond-scale ultrafast dynamic imaging while maintaining nanoscale\nresolution. Therefore, the ongoing advancements in AFM technology itself, particularly\nin speed and resolution, will significantly enhance the data readout efficiency of the\nDONLDS system.\nFluorescence readout technology has indeed demonstrated significant efficiency\nadvantages in the field of DNA storage and computing5-7. with notable advantages: 1)\nSpeed: Zhang et al.8 reported a solid-state register scheme utilizing total internal\nreflection fluorescence microscopy (TIRFM) to achieve real-time, single-molecule\ndynamic monitoring of data writing/reading processes on solid-state DNA origami\nregisters. 2) Signal Amplification: Peng Yin et al.9 reported a simple and versatile\nmolecular toolkit for rapid and cost-effective multiplexed imaging of nucleic acid\ntargets. 3) Multiplexing: Fan Zhang et al.10 reported that fluoride-based RE-doped\nupconversion microbarcodes have been successfully developed for multiplexed\nsignaling and nuclei acid encoding. Given the optical diffraction limit (approximately\n200-300 nm resolution), fluorescence labeling struggles to effectively distinguish\nadjacent sites spaced about 20 nm apart, posing significant crosstalk risks. Even super-\nresolution fluorescence microscopy11-13 currently achieved ~20 nm resolution but\nrequire minutes-long exposures per frame.\nOur developed DONLDS system employs AFM as its core readout modality. This\nchoice is driven by the need to validate the unique molecular implementation of the\nsystem’s dynamic linked-list structure. AFM is currently the only technique capable of\nproviding direct, nanoscale visualization and verification of structural morphology. Its\nirreplaceability lies in its ability to simultaneously resolve node morphology,\nconnection topology, and the spatial arrangement of data domains, these are critical\npieces of evidence required to confirm the successful implementation of dynamic\nlinked-list operations. Furthermore, the system utilizes streptavidin-biotin (SA-Biotin)\nlabeling of data domains to encode binary information. AFM can clearly resolve the\ncharacteristic physical protrusions formed by SA molecules.\nLooking ahead, we plan to explore multimodal readout strategies. For example,\nintegrating the high-precision morphological analysis capability of HS-AFM with the\nsignal amplification advantages of fluorescence labeling could establish a hybrid\nreadout platform with higher throughput.\nComment 3: Can they do an estimation calculation on how the fidelity of the\ninformation storage scales with the amount of information stored based on the data they\nalready have?\nResponse: We thank the reviewer for this important question regarding the scaling of\nfidelity in our DONLDS system. We provided a quantitative assessment of how storage\nfidelity scales with increasing information capacity.\nThrough triplicate experiments, we characterized the single-bit storage\nperformance of monomeric DON nodes. (Fig. 2c and new Supplementary Fig. 8)\nDON Storage Capacity Mean Correct Rate Single-bit Error Rate\nTypes (bits/node) (q) (p)\nTDON 8 88.49 1.54%\nCDON 8 89.01 1.43%\nRDON 12 86.73 1.22%\nNote: “Mean Correct rate” denotes the probability of a node storing all bits accurately.\nError nodes predominantly exhibit partial bit-loss rather than complete failure.\nFig. 2 c, The size of each node used by DONLDS for storing information, as well as\nits storage capacity and density. Scale bar: 50 nm.\nAs storage capacity increases, fidelity follows an exponential decay trend. This is\nparticularly pronounced in large-scale systems, necessitating strategies like redundancy\nor error correction.\nTo enhance data retrieval robustness, we employ a composite reading strategy\n(Decoding thresholds were defined as: SA connection >80% = ‘1’, <20% = ‘0’, and\n20%-80% = invalid bit): Analysis of 24 randomly selected samples (totaling 1728 bits)\nrevealed a 99.99% recovery rate when compared bitwise with the pre-defined ‘DNA-\nSTORAGE-1988’ sequence. (New Supplementary Figures 38–39)\nWhile the present study prioritizes functional validation (e.g., multi-type\ninformation storage and dynamic operations), establishing a quantitative fidelity-\ncapacity relationship remains imperative for practical DNA storage applications. We\nwill address this in future work through systematic scaling experiments and error-\ncorrection modeling.\nWe added this discussion to the revised manuscript (Page 23, Lines 544–547):\n“Future efforts will establish a quantitative model correlating fidelity with capacity\nthrough systematic scaling experiments and co-designed error correction, advancing\nthe DONLDS system from conceptual proof toward practical application.”\nComment 4: From the text it is unclear if the authors actually made the designs\nthemselves from scratch or if they were adapted from previous designs (in that case the\norigin should explicitly be cited).\nResponse: We thank the reviewer for raising this important clarification. The DNA\norigami nanostructures (TDON, RDON, CDON) were adapted from established\ndesigns in the literature, while the dynamic linkage mechanism, pointer-operation\nstrand system, and data storage methodology are entirely novel contributions of this\nwork.\nDNA origami structural designs were adapted from:\n1. Rectangular DON: following the design outlined by Rothemund. Folding DNA to\ncreate nanoscale shapes and patterns. Nature 440, 297–302 (2006).\n2. Triangular DON: following the design outlined by Hao Yan et al. DNA directed\nself-assembly of anisotropic plasmonic nanostructures. J. Am. Chem. Soc. 133,\n17606–17609 (2011).\n3. Cross-shaped DON: following the design outlined by Nadrian C. Seeman et al.\nCrystalline Two-Dimensional DNA-Origami Arrays. Angew. Chem. Int. Ed. 50,\n264–267 (2011).\nOur original contributions include:\n1. The pointer-operation strand system for programmable node linking (Figs. 1b, 3d)\n2. Dynamic memory allocation via strand displacement (Figs. 4a, 6a-b)\n3. Multi-type data encoding scheme (English/Chinese/digital, Figs. 3-5)\n4. Bidirectional linked list editing (insertion/deletion, Fig. 6c-g)\nAll structural designs are explicitly cited in the revised Supplementary: Methods\nsection 1 (Synthesis of DON nodes, Page 3).\nComment 5: Statistical information is largely missing. The author state yields of the\ncorrect assemblies, but how were they determined? How many independent\nexperiments where conducted (no error bars are shown)\nResponse: We thank you for the thorough review of our work and your valuable\nfeedback. We acknowledge that the omission of error bars in the presentation of our\nresults was an oversight during the writing process. We have supplemented the relevant\nstatistical data, including the standard deviations and error bars for each experiment, to\nmore clearly demonstrate the reliability of the results.\nIn our study, the yield of correctly assembled constructs was determined through\nmultiple independent experiments. Specifically, we performed three independent\nexperiments for each type of DON node (TDON, RDON, and CDON) to ensure the\nreproducibility and reliability of the results. In each experiment, we recorded the ratio\nof successfully assembled nodes to the total number of nodes, thereby calculating the\nassembly accuracy for each node type. The total count N used for statistics is indicated\nin the AFM images. Based on Reviewer 3’s comments, an additional SA site for\npositioning has been added to edge ‘a’ of the TDON triangle, and all corresponding\nAFM images have been revised accordingly.\nThe relevant modifications in revised manuscript:\n“The experimental data indicated that SA could effectively dock with the\npredetermined storage domains, ensuring information storage accuracies of 91.17% ±\n0.86% to 95.64% ± 2.05% for TDON nodes (Fig. 3c and Supplementary Fig. 9–11).”\n(Page 8, Lines 200–203)\n“…the instruction of linkage could be executed by introducing operation strands\nwhich generated 5 dimeric TDON nodes with an accuracy of 90.73 ± 1.36% to 92.07%\n± 1.78% (Fig. 3d and Supplementary Fig. 12).” (Page 9, Lines 210–212)\n“…the frequencies of the dimer nodes within the reaction system were 19.87 ±\n0.35% (HE), 19.43 ± 0.46% (L L ), 18.62 ± 0.31% (O W), 19.25 ± 0.32% (O R), and\n1 2 1 2\n18.99 ± 0.77% (L D), respectively (Fig. 3e and Supplementary Fig. 13).” (Page 9, Lines\n3\n218–220)\n“…The data retention accuracy of CDONs ranged from 91.17 ± 1.64% to 95.94 ±\n1.04% across three independent experiments.” (Page 11–12, Lines 263–265)\nThe revised figures and their corresponding legends include: manuscript Figure 3\nand Supplementary Figures 3-6, 9-13, and 16. Below is a display of partial data:\nSupplementary Fig. 9 | The TDON nodes represent the binary information of\nEnglish letters: ‘A’, ‘B’, ‘C’, ‘D’, ‘E’, ‘F’, ‘G’, and ‘H’. a, Schematic diagram of the\nencoding of letters A to H on TDON and their AFM diagrams. Correct samples are\nlabeled with green dots, and defective samples with red dots. Each sample size is\ndenoted as N. b, Statistical chart of the yield of English letters A to H. These eight\nTDON nodes demonstrate an efficiency rate ranging from 92.76 ± 2.22% to 95.64 ±\n2.05% in storing information. Error bars represent SD, n = 3. Scale bar: 200 nm. Source\ndata are provided as a Source Data file.\nThe images have been replaced in Figure 9 of the revised Supplementary. (Page 13)\nSupplementary Fig. 12 | The TDON nodes are encoded with binary information\nrepresenting the English letters: ‘HE’, ‘L L ’, ‘O W’, ‘O R’, ‘L D’. a, AFM images\n1 2 1 2 3\nof the English letters: ‘HE’, ‘L L ’, ‘O W’, ‘O R’, ‘L D’. Correct samples are labeled\n1 2 1 2 3\nwith green dots, and defective samples with red dots. Each sample size is denoted as N.\nb, The yield for storing the letter ‘HE’ in dimer TDON nodes is 92.54 ± 0.99%; for\n‘L L ’ it is 90.87 ± 2.16%; for ‘O W’ it is 90.73 ± 1.36%; for ‘O R’ it is 92.07 ± 1.78%;\n1 2 1 2\nand for ‘L D’ is 91.26 ± 2.06%. Error bars represent SD, n = 3. Scale bar: 200 nm.\nThe images have been replaced in Figure 12 of the revised Supplementary. (Page 16)\nSupplementary Fig. 16 | CDONs stored the number from zero to nine. a, AFM\nimage of CDONs. Correct CDONs are marked in green frames. Incorrect CDONs are\nmarked in red frames. Each sample size is denoted as N. Scale bar: 200 nm. b, The yield\nof correct CDONs are ranging from 91.17 ± 1.64% to 95.94 ± 1.04% (n =3 experiments).\nError bars show the standard deviation of the sample. Scale bar: 200 nm. Source data\nare provided as a Source Data file.\nThe images have been replaced in Figure 16 of the revised Supplementary. (Page 20)\nComment 6: If the receiver does not know what information is encoded, how do you\ndistinguish between a bad AFM image or a dirty tip, where not every streptavidin can\nbe seen and an actual change in information? Do they use automated analysis for\nreadout? This would help avoid bias.\nResponse: We sincerely appreciate this critical question regarding AFM image\ninterpretation. Currently, our readout process relies on manual analysis, and we\nacknowledge that automated methods would further enhance objectivity. To address\nambiguity between true information changes and imaging artifacts, we employ a multi-\nlayered validation strategy.\n1. Statistical confidence through redundancy\nTo ensure data reliability, each data pattern is replicated across multiple independent\nnanostructures, such as having at least five identical DON nodes per encoded datum.\nThis redundancy helps distinguish true information from artifacts, as artifacts like\ntip contamination tend to appear randomly, while genuine information patterns\nshow consistency across replicates. (e.g., Supplementary Fig. 9–11). Consequently,\naccuracy rates, such as the 91-95% achieved for TDON, are derived from\npopulation-level analysis, which minimizes bias from single images.\n2. Height-based signal validation\nThe loading of SA onto DNA origami produces a characteristic height signature of\napproximately 2.5 to 4 nanometers under air conditions, which is measurably higher\nthan the typical height range of 1.5 to 2 nanometers observed for bare DNA origami\nstructures. We apply a strict threshold (>2.5 nm) to confirm SA presence\n(Supplementary Fig. 29c). Locations below threshold are recorded as ‘0’ regardless\nof expected encoding. This physical metric provides an objective criterion\nindependent of expected patterns.\n3. Composite reading strategy for data storage sites\nThe decoding protocol for a given data storage site uses the following thresholds: a\nstreptavidin (SA) connection percentage exceeding 80% decodes the data domain\nas a binary ‘1’, while a percentage below 20% decodes it as a binary ‘0’.\nPercentages ranging between 20% and 80% result in the data domain being\nclassified as an invalid bit. (Supplementary Fig. 29e, 30e, 39). The 20–80% buffer\nzone isolates unambiguous signals, reducing error propagation.\nWe recognize that manual analysis is subjective and can be prone to bias. Therefore,\nwe agree that implementing automated analysis for readout would significantly\nimprove the robustness and objectivity of our system. Automated analysis could involve\nimage processing algorithms to identify and quantify SA binding, as well as statistical\nmodels to assess the confidence level of the data. While automated analysis is not\ncurrently part of our workflow, we plan to explore and incorporate such methods in\nfuture research to enhance the reliability and scalability of the DONLDS.\nSupplementary Fig. 29 | RDON node storing the Chinese message of ‘DAO KE\nDAO’. a, Flowchart of Chinese characters being written into an RDON node. b, AFM\nimage of an RDON node with Chinese character zone-bit codes written. Scale bar: 350\nnm. c, Height map of the RDON node with Chinese character zone-bit codes written.\nScale bar: 50 nm. d, RDON nodes with complete data are marked with red boxes, while\nthose with missing data are marked with blue boxes. Scale bar: 50 nm. e, Yield statistics\nfor each binary code of the Chinese character area codes for ‘DAO KE DAO’. Source\ndata are provided as a Source Data file.\nReviewer #3\nThis article by Zhang et al. describes how DNA origami nanostructures can be used for\n‘linked data storage’. It is not the first paper of its kind where DNA origami is used for\nsome way of computing or data storage but it is a field that has become very active after\n20 years of being ignored by many. Before acceptance of this manuscript, we\nrecommend major revisions as outlined below.\nResponse: We sincerely thank Reviewer #3 for their thorough evaluation and\nconstructive feedback. We acknowledge the reviewer’s point regarding the evolving\nactivity in the DNA origami field for computing and data storage applications. We\nconfirm that major revisions have been undertaken to address the concerns raised,\nstrengthening the manuscript.\nKey enhancements, reflected throughout the revised text and figures, we believe\nthese revisions have elevated the manuscript’s quality and impact. We are grateful for\nthe opportunity to improve our work based on the reviewer’s valuable insights.\nMain concerns:\nComment 1:\nComment 1.1: The biggest concern I see is if the orientation of the nodes can really be\nreliably determined for correct read out of the bit values. In general, the DONs can land\nin different orientations and according to Fig.2c for TDONs also with either of the two\nsurfaces oriented towards the substrate and this leads to read out problems, when some\nof the bits in a node are set to 0. Fig. 3b implies single TDONs can be identified\ndeciphered into the letters they are coding for, but in Fig 3c, there are multiple\nambiguous codings, when taking into account rotations and filipping of the DONs: If\nyou flip the DON for J, if matches the one for D, despite the ‘symmetry breaking’ 010\nsequence, the same goes for M and Y (AFM images for M and Y are the same). J and\nQ are connected through a 120 deg rotation, also Y and K. I do understand that the\nsymmetry is additionally broken by the pointer strand domains, so in most cases of\nlonger words, the readout wouldn’t be ambiguous, but it is not clear to me, that this is\ntrue for every combination of letters, especially if we consider only two letter syllables.\nI also do not understand how the direction of reading of the nodes is determined in the\ncase of symmetrical TDONs. For instance, the word MH, can only be read in this\ndirection. However, if it is flipped to face the substrate with the top side, the letters\nbecome YH. What is more, it can be read also in the opposite direction, yielding the\nword MK. This might not be an issue for longer words, but it should still be\ndiscussed/explained.\nResponse: We sincerely thank the Reviewer for their insightful comments regarding the\npotential directional ambiguity in node interpretation during data readout. We\nacknowledge that the original design of the TDON could lead to rotational/flip\nambiguities for certain letters (e.g., J/Q, M/Y/K).\nTo address this issue, we have placed an additional Streptavidin (SA) tag on the\ninner edge of side “a” of each TDON node (Review Figure 2a and NEW Figure 3a).\nThis tag serves as a physical orientation anchor, breaking the rotational symmetry. The\nnew description of orientation code domain has been added to the revised manuscript\n(Page 8, Lines 190-194): “To ensure unambiguous spatial orientation, we used a fixed\n3-bit orientation code (‘010’) and a streptavidin (SA) marker on the inner edge of side\n“a” to break rotational symmetry. This combination eliminates ambiguities from\norigami flipping and rotational misalignment, followed by a 5-bit alphabet coding set\nfor letter differentiation.”\nAs illustrated in Review Figure 2b, the original problem was: a letter Q, when\nrotated by 120°, aligns with J. Similarly, letter M, when flipped and/or rotated, could\nmatch K or Y. The new Q (featuring the new SA tag) no longer aligns with new J.\nFurthermore, M, K, and Y are now distinguishable under all transformations\n(flip/rotation).\nConsequently, with the updated alphabet design and AFM (NEW Figure 3c), no\noverlap occurs between any letters under rotations (0°-360°) or flips.\nThe reviewer’s comment precisely identified a critical design element for ensuring\nreliable data readout in our DONLDS system. By introducing a fixed, asymmetric\norientation anchor on the inner edge of the “a” side of each TDON node, we\nfundamentally eliminated potential ambiguities arising from rotational and flip\nsymmetry during AFM readout. This anchor, combined with the inherent directionality\nof pointer linkages and the clear definition of the head node/chain direction, ensures\naccurate and unambiguous readout of data within individual nodes and the sequence of\ndata in linked lists. We again sincerely thank the reviewer for this insightful and highly\nvaluable comment, which significantly enhances the robustness and clarity of our\nDONLDS system’s readout mechanism.\nData for review only: Review Figure 2: a, An additional Streptavidin (SA) tag on the\ninner edge of side “a” of each TDON node. b, The original letter Q, when rotated 120°\nin a plane, will coincide with the original letter J. A new registration mark is added to a\nspecific location on the letter Q, the new Q will no longer be the same as J. The original\nletter M, when rotated 120° in a plane and flipped 180°, will coincide with the original\nletter K. The original letter Y, when rotated 240° in a plane, will also coincide with the\noriginal letter K. the new letters M, K, and Y will no longer coincide with each other.\nFig. 3 | Encoding of English Letters Utilizing TDON Nodes. a, A schematic diagram\nof the TDON data domain and pointer domain is provided. In the floor plan, the area\nwithin the grey line frame represents the attachment position of SA, which is the data\ndomain, and the area within the blue frame was the pointer domain of TDON. In the\nthree-dimensional view, the black short cylinders represent the orientation code domain,\nand the orange cylinders represent the Alphabetic code domain. The data in the data\ndomain is read in a clockwise direction. b, A flowchart for the writing and reading\nprocess of English letters is illustrated. The figure describes the English alphabet\nalongside its corresponding binary code table and provide a stepwise depiction of the\nencoding procedure for the letter ‘A’ within the TDON node. c, The AFM images\nshowcase the storage of all 26 English letters on the TDON nodes. d, The assembly\nprocess of ten different TDON nodes is depicted. The AFM images illustrate the\nsynthesis of five distinct dimer letter combinations: ‘HE’, ‘L L ’, ‘O W’, ‘O R’, and\n1 2 1 2\n‘L D’. e, The yield statistics graph shows their average yield in the overall system to be\n3\n18.62 ± 0.31% ~ 19.87 ± 0.35%, with a node mismatch rate of 3.83 ± 0.95%. The\nsample size is 477. Error bars represent SD, n = 3. Scale bar: 50 nm. Source data are\nprovided as a Source Data file.\nThe images have been replaced in Figure 3 of the revised manuscript. (Page 10, Line\n222)\nComment 1.2: For the CDONs the authors explain that the presence of a scaffold loop\nhelps to break the symmetry and enables unambiguous read-out. This seems also to be\nthe case for RDON dimers, but it is not clearly explained in the text. If so, this would\nbe enough in combination with the blue ‘orientation domain’ from Fig. 5 to mark the\nproper orientation of the RDONs, but it does not help with orienting the RDON\ntetramers, which do not have orientation domains and could be flipped to their top side\nto face the substrate. On a related note, in the paragraph starting with line 313, the\nauthors use tetramers of RDONs to encode longer phrases with chinese characters. Why\nis there no need for an ‘orientation domain’ as in the case of RDON dimers from the\nprevious paragraph? This should be clarified in the text.\nResponse: We sincerely appreciate the reviewer’s insightful comments. We fully concur\nwith the reviewer’s perspective on the role of the scaffold loop in CDON. It indeed\nensures unambiguous signal readout by breaking structural symmetry. We similarly\naffirm that this principle extends to the RDON dimer. Regarding the orientation domain\nhighlighted in Figure 5, its design purpose is to synergize with the scaffold loop to\nmaintain the correct orientation of the RDON dimer upon substrate adsorption.\nTo enhance reader comprehension of this directional control mechanism, we have\nclarified the revised manuscript (Page 14, Lines 321–325): “Analogous to the scaffold\nloop in CDON, the RDON dimer employs its blue orientation domain to break\nstructural symmetry (Fig. 5a). The orientation domain cooperates with the scaffold loop\nto enforce uniform node orientation during substrate adsorption, eliminating data\nreadout ambiguity caused by structural flipping.”\nConcerning the RDON tetramer, its core objective is modular expansion for\nenhanced storage capacity. The tetramer design focuses on efficiently integrating the\nChinese character domain of multiple RDON monomers (Note: This construct excludes\nthe index domain and orientation domain).\nWe have clarified this in the revised manuscript (Page 14–15, Lines 336–343):\n“Beyond monomeric RDON nodes, we leveraged RDON’s modular expandability to\naugment storage capacity specifically within the Chinese character domain (excluding\nthe index and orientation domains). We demonstrated storage of the traditional Chinese\nmaxim ‘DAO KE DAO FEI CHANG DAO’ from the Tao Te Ching using an RDON\ntetramer, achieving 48-bit capacity at 222.22 Gbit/cm2 density. This resolves the long-\ntext storage bottleneck, and the modular architecture underpins future chain or grid-\nbased large-scale DONLDS system (Fig. 5d, Supplementary Figs. 29–30).”\nFig. 5 | Utilized RDON nodes for storage of Chinese characters. a, Diagram illustrating\nthe division of index, orientation, and Chinese character domains within a dimer RDON\nnodes. b, The process for storing and retrieving Chinese characters. Initially, the\ncharacter ‘HOU’ is identified, followed by the retrieval of its zone-bit code, which is\ntranscoded into binary and inscribed within the RDON node. After the information is\nread using an AFM, the binary code is reconverted back to the zone-bit code, ultimately\nleading to the retrieval of the character ‘HOU’. c, The Chinese character zone-bit code\nand RDON nodes store eight Chinese characters arranged in the following reading order:\n‘HOU DE’; ‘HONG YI’; ‘QIU SHI’; ‘DU XING’. These characters represent the\nmeanings of ‘profound virtues’, ‘magnanimous and firm’, ‘seeking truth’, and\n‘persevering practice’. d, Tetramer RDONs with expanded storage capacity have a\nstorage capacity of 48 bits and a storage density of 222.22 Gbit/cm2. Storing the\nChinese phrase in the tetrameric RDONs: ‘DAO KE DAO, FEI CHANG DAO’.\nAnalysis of AFM images show that the information stored in the two DONs is\nsuccessfully decoded and transformed into a phrase from the Chinese book Tao Te\nChing: ‘DAO KE DAO, FEI CHANG DAO’. Scale bar: 50 nm.\nThe images have been replaced in Figure 5 of the revised manuscript. (Page 15, Line\n345)\nComment 2: There is a fundamental problem if one desires to encode data storage by\nlinking DNA origami structures: Finding reliable and practically orthogonal sequences.\nOn paper two different sequences look great (e.g. GTTGTTTT vs. TTTTTTTT) , but\nsuch sequences will easily bind to any sequence containing many As (like AAAAAA).\nEspecially if there are plenty of such sequences with slight complementarity next to\neach other on an origami they bind like velcro. In other words: just being orthogonal\nsequences on paper does not exclude them binding to each other at room temperature.\nThis requires discussion. Along this line: To use the DONLDS seriously as data storage\nsystem, a base of pointer and operation staples should be made. It would be beneficial\nto discuss how the needed number of strands scales with the number of bits the system\nis able to store.\nResponse: We appreciate the reviewer’s insightful comment on the challenges of\nfinding truly orthogonal DNA sequences for reliable data storage. We agree that\ntheoretical orthogonality does not always translate to practical orthogonality, especially\nin complex systems with multiple potential binding sites. The ‘velcro effect’ described\nby the reviewer is a valid concern.\nWithin the DONLDS system, the implementation of each unique “linking\ninstruction” requires a set of orthogonal pointer strands and their complementary\noperation strands (executing the instruction). During the initial design phase, we\nexcluded all pointer strands containing ≥5 consecutive identical bases (e.g., TTTTT\nor\nAAAAA) to eliminate the risk of nonspecific binding triggered by such “sticky”\nsequences.\nFurthermore, we systematically evaluated the orthogonality potential of the\ndesigned 120 pointer strands (16 nt) in a practical application context (Supplementary\nSection 8 Table 3, highlighted sequences). To this end, we performed all possible\npairwise sequence alignments and constructed a sequence similarity score matrix based\non Hamming distance (i.e., scoring only for identical bases at the same position),\nfollowed by visualization (New Supplementary Fig. 3). The resulting heatmap clearly\nshowed that only the diagonal region (representing self-alignment) exhibited the\nhighest score (16). Statistical analysis (histogram) of the scores for non-diagonal\nsequence pairs further confirmed that >99.27% of pairs had a similarity score ≤8\n(i.e.,\nsequence similarity < 50%). This result indicated extremely low similarity between the\nvast majority of sequence pairs, collectively ensuring a low risk of cross-reactivity in\nthe overall sequence design.\nWe have clarified this in the revised manuscript (Pages 4–5, Lines 113–118): “We\nassessed orthogonality among the 120 designed 16-nt pointer strands (Supplementary\nTable 3) by computing all pairwise Hamming distances. Visualization of the similarity\nmatrix (Supplementary Fig. 3) showed that more than 99.27% of off-diagonal pairs\nscored ≤8 (<50% similarity), demonstrating low inter-sequence similarity and cross-\nreactivity risk across the design.”\nSupplementary Fig. 3 | a, Score Matrix Visualization of 120 16-nt pointer strands. b,\nStatistical analysis (histogram) of the scores for non-diagonal sequence pairs. Source\ndata are provided as a Source Data file.\nThe images have been replaced in Figure 3 of the revised Supplementary. (Page 27)\nWe agree that clarifying the relationship between DNA strand usage and storage\ncapacity is essential. In our system, data storage occurs within individual nodes, while\ndata linkage is managed dynamically through operation strands. This dynamic\nallocation, enabled by DNA strand displacement, eliminates the need for contiguous\nmemory blocks as shown in Supplementary Fig. 2. These pointer strands and operation\nstrands are detachable, and in practical application processes, they can be reused.\nFor example, to store 1Kbit of data, we divide the data into 10 layers, and each layer\nrequires the following number of pointer strands and operation strands:\nSpecies Storage type Capacity/node Layer Storage P O\nt t\nTDON English letters 8 Bit 10 1Kbit 144 144\nRDON Chinese characters 12 Bit 10 1Kbit 100 100\nCDON Arabic numerals 8 Bit 10 1Kbit 144 144\nNote: Pointer strands types (P); Operation strands types (O)\nt t\nNaturally, as data volume increases, we can augment the number of data hierarchy\nlayers, thereby reducing the demand for pointer strands variety.\nComment 3: Also in this context: The design scheme of the pointer and operation\nstrands presented in Fig. 1b is cryptic. Neither the main text nor the figure caption\nexplain how these non binary numbers (and letters) correlate to the 16nt DNA\nsequences. Is there any logic (does a number at a certain position denote a specific\nnucleotide?) or how are the sequences chosen? Give examples.\nResponse: We apologize for the lack of clarity in explaining the design scheme of the\npointer and operation strands in Figure 1b.\nThe non-binary numbers (and letters) in Figure 1b are simply identifiers for\ndifferent pointer and operation strands (Review Figure 3a). There is no direct\ncorrelation between the numerical value or letter and the nucleotide sequence.\nDuring the initial design of the DNA pointer strand sequences, we excluded all\npointer strands containing ≥5 consecutive identical bases to avoid the risk of non-\nspecific binding. Sequences exhibiting high similarity were also eliminated by\ncomparing the Hamming distance between sequences. In addition, the sequences were\nchosen using NUPACK to ensure orthogonality and minimal cross-reactivity. We\nperformed “one-pot” binding simulations using NUPACK software. This simulation\nanalyzed a mixture containing multiple pairs of pointer and operation strands under\nroom temperature conditions. The simulation results confirmed that all pointer strands\nspecifically bound to their corresponding operation strands, with no detectable\nsignificant nonspecific hybridization (Review Figure 3b).\nWe provided a more detailed explanation in the revised manuscript (Page 4, Lines\n107–108): “…which were situated at the edges of DON nodes and adorned with\ngrouping sequence coding (Supplementary Table 3).”\nData for review only: Review Figure 3: a, “one-pot” binding simulations using\nNUPACK software. b, DNA MFE proxy structure.\nComment 4: Why are only TDON dimers used to encode two letters at a time instead\nof the whole ‘Helloworld’ phrase in a single sequence of nodes?\nResponse: We sincerely appreciate the reviewer’s insightful question regarding our use\nof dimeric TDON nodes for dual-letter encoding rather than storing the complete\n“HELLO WORLD” phrase in a single node. This experimental design was strategically\nimplemented to rigorously validate two critical properties of our molecular\nprogramming system.\n1. Multi-strand orthogonality\nStoring the entire phrase in one sequence nodes, eliminating cross-reactivity\nevaluations among multiple pointer strands and operation strands. By decomposing\n“HELLO WORLD” into five independent letter pairs (‘HE’, ‘L L ’, ‘O W’, ‘O R’,\n1 2 1 2\n‘L D’), we created a complex reaction environment containing 10 distinct monomeric\npairing specificity under high combinatorial complexity. As demonstrated in Fig. 3e\nand Supplementary Fig. 13, the system achieved remarkable orthogonality: Formation\nyields of target dimers ranged between 18.62% ± 0.31% and 19.87% ± 0.35%. Overall\nnode mismatch rate was only 3.83% ± 0.95% (N=477) Connection accuracy reached\n96.17% ± 0.95% (NEW Supplementary Fig. 13c), confirming minimal cross-talk\nbetween heterologous pointer/operation strand pairs.\n2. Instruction execution fidelity\nThe dimerization approach directly tests the system’s capacity to execute linkage\ncommands. Introduction of operation strands successfully generated all five target\ndimers with yields ranging from 90.73% ± 1.36% to 92.07% ± 1.78% (Fig. 3d and\nSupplementary Fig. 12b). Critically, AFM imaging (Supplementary Fig. 13b) verified\nformation of intended dimeric structures.\nThis approach provides essential validation for future scaling of DONLDS system.\nOur dimeric strategy delivers indispensable metrics on: orthogonality limits in multi-\ninstruction systems; DNA strand-level addressing specificity; Real-world error rates\nduring concurrent operations. The robust yields (>90%) and specificity metrics (>96%)\nconfirm TDON suitability as foundational elements for programmable molecular data\nstructures.\nSupplementary Fig. 13 | Experiment on the specificity of connection between\n0peration and pointer strands. a, Within the TDON pointer strands pool, an intricate\narray of five sets of DNA strands has been meticulously arranged, with each set\ncomprising twelve distinct DNA strands. The operation strands are tasked with base-\npairing complementarity to two pointer strands; their sequence design is tailored based\non the sequences of the pointer strands at both ends of the connecting node, with an\noverall length of 36 nt. The segment that binds to one end of the pointer strand measures\n16 nt in length. we have prepared ten diverse TDON nodes and introduced the\ncorresponding operational strands for the matching trials. The anticipated outcome, as\nper the experimental design, is the formation of five dimeric TDON structures. b, The\nAFM image reveals a blend of five distinct triangular nodal configurations: ‘HE’,\n‘L L ’, ‘O W’, ‘O R’, and ‘L D’. c, The TDON’s makeup shows the distribution of the\n1 2 1 2 3\nfive storage node types, along with the ratio of nodes not part of these types. e, The\nyield statistics graph shows the frequencies of the dimer nodes to be 18.62 ± 0.31% ~\n19.87 ± 0.35%, with a node mismatch rate of 3.83 ± 0.95%. The sample size is 477.\nError bars represent SD, n = 3. Scale bar: 200 nm. Source data are provided as a Source\nData file.\nThe images have been replaced in Figure 13 of the revised Supplementary. (Page 17)\nComment 5: The authors claim a high information density, which is true locally for\neach DON, but in reality each object, or data string is produced in many copies. The\neffect of this redundancy on the information density should be be taken into account in\ndiscussion.\nResponse: We thank the reviewer for their insightful comments. We fully concur that\nthe impact of redundant replicas on the actual information density is a critical issue\nwarranting in-depth discussion within DNA storage technology.\nIn response, we have added the following passage to the conclusions chapter of\nthe revised manuscript (Page 22, Lines 523–527): “Although a single DON achieves\nhigh local density, system-level density is reduced by essential replicas. This\nredundancy counters stochastic DNA self-assembly errors, ensuring molecular data\nfidelity, which is a crucial trade-off for reliability. Thus, DONLDS delivers node-level\ndensity, while system-level gains depend on fabrication optimization and algorithmic\nadvances.”\nComment 6: Data reliability and streptavidin-encoding of 0 and 1: how to deal with\nerrors? DNA origami researchers know that often staples or extensions are missing in\nany given DNA origami, which is also reflected in ‘information storage accuracies of\n92.31%~96.61% for TDONS’. I expect those to be worse for RDONS, e.g. most\nRDONs in Fig. 2C are not completely covered.\nResponse: We sincerely appreciate the reviewer’s insightful critique regarding the\ninherent structural imperfections in DONs and their crucial implications for data storage\nreliability. We fully concur with the reviewer that structural defects (missing staples,\nmisfolds) are intrinsic to current DNA origami fabrication. These defects can manifest\nas missing Streptavidin (SA) molecules at intended binding sites (data domains),\npotentially leading to misinterpretation of a stored ‘1’ (SA present) as a ‘0’ (SA absent).\nWe have implemented a multi-layered strategy to manage these errors and ensure robust\ndata recovery.\n1. Height Validation\nWe use objective physical criteria to confirm SA binding: a height signature of\n~2.5-4 nm. Sites below this threshold are recorded as ‘0’ regardless of expectation,\nproviding another layer of defense against misinterpreting imaging artifacts or\nstructural defects as valid ‘1’. (Supplementary Fig. 21–28, 29–30c)\n2. The Composite Readout Strategy & Invalid Bit Mechanism\nWe achieve data recovery through a composite readout strategy that leverages\ncross-validation of signals from multiple node units within the polymeric architecture.\nBased on the observed SA connection percentage, data decoding follows a three-tiered\nthreshold criterion: sites with >80% SA binding are decoded as binary ‘1’; those with\n<20% binding are decoded as binary ‘0’; and sites exhibiting 20-80% binding are\ndesignated as ‘Invalid Bits’. By ensuring only high-confidence data contributes to final\ninformation reconstruction, it provides a fundamental safeguard for system-level data\nintegrity. (Supplementary Fig. 29-30e, 38-39)\nSupplementary Fig. 30 | RDON node storing the Chinese message of ‘FEI CHAN\nGDAO’. c, Height map of the RDON node with Chinese character zone-bit codes\nwritten. e, Yield statistics for each binary code of the Chinese character area codes for\n‘FEI CHAN GDAO’. Source data are provided as a Source Data file.\nWe acknowledge the reviewer’s specific concern regarding RDON coverage in\nFigure 2c. The imperfect SA coverage visible in some RDONs within Figure 2c. We\nhave replaced the AFM image of the RDON in Figure 2c.\nSimultaneously, we quantified the yield of RDON nodes loaded with 12 SA\nmolecules. RDONs with all sites successfully loaded are marked with blue boxes (yield:\n86.73 ± 1.16%), while defective RDONs are marked with red boxes (yield: 13.27 ±\n1.16%). (Review Figure 4)\nFig. 2 | c, The size of each node used by DONLDS for storing information, as well as\nits storage capacity and density. Scale bar: 50 nm.\nThe images have been replaced in Figure 2c of the revised manuscript (Page 7, Line\n173)\nData for review only: Review Figure 4: RDONs with all sites successfully loaded are\nmarked with blue boxes, the yield is 86.73 ± 1.16%, while defective RDONs are marked\nwith red boxes, the yield is 13.27 ± 1.16%. Error bars represent SD, n = 3. Scale bar:\n100 nm.\nMinor comments:\nComment 1: It could be good to shortly define hot and cold storage. One has a rough\nidea about it, but the broad readership of Nature Commun. could appreciate this.\nResponse: We thank the reviewer for this suggestion. We have added concise definitions\nin the revised manuscript (Page 2, Lines 45–49): “This characteristic renders current\nDNA storage technologies particularly adept at preserving cold data (data accessed\ninfrequently, prioritizing high-density, long-term archival). However, the future\ntrajectory of DNA storage is to preserve hot data (data requiring frequent, rapid access\nand modification) …”\nComment 2: line 42: With the development of techniques ... - what kind of techniques?\nResponse: We thank the reviewer for highlighting this ambiguity. As suggested, we\nhave clarified the scope of “techniques” in the revised manuscript (Page 2, Line 42):\n“With the development of advanced DNA synthesis and sequencing techniques...”\nComment 3: lines 86-87: The way it is presented, it is not clear what is meant with\n‘DNA helix ...’ and ‘DNA storage ...’. Maybe: ‘...ability of a linked list based on DONs\nto store the string ‘DNA helix 1952’ and edit it with data deletions and insertions for ...’\nResponse: Thank you for your suggestion. This will more accurately express the content\nof our research. We agree that the original wording was not clear enough. We adopt\nyour suggestion and revised manuscript (Page 4, lines 89–90) to: “...the ability of a\nlinked list based on DONs to store the string ‘DNA helix 1953’ and edit it with data\ndeletions and insertions...”.\nComment 4: line 112/Supl. Fig. 2 - it is not clear how these pointers work - what are\nthe physical positions of the DONs in a memory unit in Fig.S2 supposed to represent?\nHow can one tell apart the different nodes of the same type? ‘N’ pointer is not defined\nResponse: Thank you for pointing out this issue. We acknowledge that the working\nprinciple of the pointers and the physical positions of the DONs were not clearly shown\nin Supplementary Figure 2.\nPhysical positions of DONs: In Supplementary Figure 2, the physical positions of the\nDONs represent their logical order in the storage unit, not their actual physical locations.\nThe DONLDS system allows for non-contiguous storage, so DONs can be physically\nlocated in different positions as long as they are correctly connected via pointers.\nDistinguishing nodes of the same type: Nodes of the same type are distinguished by the\ndifferent data and pointer sequences they carry. Each node has a unique pointer\nsequence that determines how it connects to other nodes.\n‘N’ pointer has been defined in the revised Supplementary Figure 2: “‘N’\nrepresents the logical address of the next node.” Supplementary Page 6.\nComment 5: line 140: ‘... while the non-biotin labeled staples were defined as the code\n‘0’’ - If I understand correctly (e.g. in the case of RDON) only 12 out of the 216 staples\nare potentially modified with biotin, so not every staple which is not biotin labeled\nserves as a 0 binary value. Also in the caption (and in the main text) it could be better\nexplained that the red dots in Fig.2a are places where SA is potentially attached,\ndefining either a 0 or 1 bit.\nResponse: Thank you for your keen observation. Your understanding is correct; not all\nunlabeled biotin staples represent the binary value ‘0’. Only unlabeled biotin staples\nlocated at the specified data domain positions are defined as ‘0’.\nTo make it more accurate, we have revised the description of manuscript (Page 6,\nlines 149–151): ‘... we implemented connections at SA linked domains (red dots),\ncoupling streptavidin (SA) with biotin-modified data strands, only unlabeled biotin\nstaples located at the SA linked domains are defined as code ‘0’...’\nIn addition, we state in the caption of Figure 2a that the red dots represent the\npositions where SA may attach, which define a ‘0’ or ‘1’ bit in revised manuscript\n(Pages 7–8, Lines 176–178): “Red dots indicate potential SA conjugation sites for data\nencoding, where SA presence/absence defines bit states (1/0).”\nComment 6: line 148: ‘...each DON node was perfectly aligned with SA ...’ What do\nyou mean by ‘perfectly aligned’? Perhaps ‘modified’ or ‘coupled’ or similar?\nlines 200-201: it would probably be beneficial to explicitly state that this ‘simultaneous\nconduction of instructions’ was done by mixing all ten monomer storage nodes with all\nthe operation strands - this might not be obvious to a person not from the DNA\nnanotechnology field.\nResponse: We thank the reviewer for this precise suggestion. The phrase “perfectly\naligned” was indeed suboptimal for describing the biochemical conjugation process.\nWe have replaced it in the revised manuscript (Page 6, Lines 159–160):\n“…Ultimately, AFM images confirm site-specific conjugation of SA to biotin-modified\ndomains…”.\nIn addition, we have explicitly stated that ‘simultaneous conduction of instructions’\nwas achieved by mixing all ten monomer storage nodes with all the operation strands.\nWe have added it in the revised manuscript (Page 9, Lines 213–215): “…we conducted\ninstructions by co-incubating all ten monomer storage nodes with their corresponding\noperation strands in a single reaction system…”.\nComment 7: In Lines 204-206: I would avoid calling these ~20% values ‘accuracies’,\nif I understand correctly, these are frequencies. I assume in this experiment the expected\nfrequencies are 20% for each of the dimers? If so, the accuracy of dimer formation for\neach dimer is close to 100%, not 20%.\nResponse: Thank you for pointing out this issue. These values are actually frequencies,\nnot accuracies. We have changed ‘accuracies’ to ‘frequencies’ in the revised manuscript:\n“…the frequencies of the dimer nodes within the reaction system were…”. (Page\n9, Line 218)\n“…e, The graph shows the frequencies of the dimer nodes…” (Page 11, Line 235)\nComment 8: line 232: toeholds & toehold-mediated strand displacement is introduced\nwithout any explanation or background\nResponse: Thank you for pointing out this issue. We have added a definition in the\nrevised manuscript (Page 11, Lines 250–252) to help readers better understand their\nworking principles:\n“…CDON nodes via toehold-mediated strand displacement, which is a\nfundamental mechanism in DNA nanotechnology where transient binding at short\nsingle-stranded “toehold” regions initiates branch migration to displace hybridized\nstrands…”\nComment 9: Fig. S14 shows 8 positions for the ‘bits’ on the CDON, but only 4 are used\nto encode the arabic numerals and it its not clear which 4.\nResponse: Thank you for pointing out this issue. We have clearly indicated in the legend\nof Supplementary Figure 15 that the 4 positions used to encode Arabic numerals are\nArabic numeral code domains from 1 to 4.\nRevised manuscript (Page 11, Lines 260–262): “We selected four dedicated coding\ndomains (positions 1-4 in Supplementary Fig. 15) within CDON nodes to implement\n4-bit binary encoding for digital information storage.”\nSupplementary Fig. 15 | a, Within the CDON node, the delineation of functional areas\nis distinctly demarcated. The region encircled by a red border is designated as the data\ndomain, tasked with the preservation of specific data; conversely, the area outlined in\nblue constitutes the domain of the pointer strands, which assumes the responsibility of\ninterlinking the various nodes via pointers. b, The precise positioning of the CDON\nnode pointer strands, along with its corresponding Arabic numeral coding, is elucidated.\nAdditionally, a meticulous notation of the encoding sequence for the CDON nodes is\nprovided. Moreover, the ingeniously designed loop structure within the CDON plays a\npivotal role in the identification and localization of data.\nThe images have been replaced in Figure 15 of the revised Supplementary. (Page 19)\nComment 10: In lines 350–351 the authors introduce P and S as labels for different\nnodes without any explanation of the meaning. Because of abundance of other letters\nResponse: Thank you for your suggestion. We explicitly explain the meaning of P and\nS in lines 355–357. P represents the ‘previous’ node, and S represents the ‘subsequent’\nnode.\nRevised manuscript (Page 16, Lines 374–376): “…which generated the\ndisconnection of nodes 2 (P, denoting ‘previous’ node) and 4. Then, two new linking\nstrands were added to form the linkage of the pointer of node 3 (S, denoting ‘subsequent’\nnode) with that of nodes 2 (P) and 4 …”\nComment 11: in Fig. 6 with different meanings (N & Y for no and yes, T, R & C for\ndifferent types of nodes and the encoded english letters) this is confusing, so please\nexplain the meaning and perhaps consider a different label for the deleted and inserted\nnodes. In Fig 6a, it would be clearer to the reader if ‘no’ and ‘yes’ were used instead of\n‘n’ and ‘y’\nResponse: Thank you for your suggestion. We used ‘No’ and ‘Yes’ instead of ‘n’ and ‘y’\nin Figure 6a to improve clarity.\nFig. 6 a, A flowchart for the insertion of DON nodes.\nThe images have been replaced in revised Figure 6a of the revised manuscript. (Page\n19, Line 443)\nIn the linked list, T, R and C represent different types of nodes. Specifically, they\nrespectively refer to TON, RDON and CDON.\nWe have added supplementary explanations to the caption of Figure 6d in revised\nmanuscript (Page 19, Lines 448–449): “T, R, and C denote distinct DNA origami\nnanostructure nodes: triangular (TDON), rectangular (RDON), and cross-shaped\n(CDON).”\nComment 12: line 384: it is not clear what is meant by ‘a specialized SA connection\ndomain’ that serves as the identifying characteristic of the head node\nResponse: Thank you for pointing out this issue. We refined the language on line 384\nto enhance its clarity. The term ‘dedicated SA connection domain’ alludes to the specific\nregion within the triangular DON framework that is allocated for facilitating SA\nconnections. This area not only functions as a positioning indicator but also serves as a\ndistinct identifier for the head node, streamlining the overall architecture and improving\nfunctionality.\nRevised manuscript (Page 17, Lines 408–409): “A SA connection domain was\nembedded within the edge “a” of TDON as an identifying feature of the head node.”\nComment 13: line 432: ‘We demonstrated ... 8 Chinese characters ...’ While it is true\nthat the authors demonstrated only a limited selection of chinese characters, this system\ncould in principle encode any chinese character. I think the authors should state this\nclearly so that this is not taken as a limitation of the DONLDS.\nResponse: Thank you for your suggestion. We revised the wording in line 432 to clearly\nstate that the DONLDS system can, in principle, encode any Chinese character, not just\nthe 16 Chinese characters (“HOU”, “DE, “HONG”, “YI”, “QIU”, “SHI”, “DU”,\n“XING”, “DAO”, “KE”, “FEI”, “CHANG”, “LUO”, “XUAN”, “CUN”, “CHU”) we\ndemonstrated.\nRevised manuscript (Page 20, Lines 466–468): “We demonstrated the storage of\nGB2312 code, confirming the DONLDS’s efficiency and accuracy.”\nComment 14: The manuscript would benefit from proof-reading. Most of the text is\nwritten in past tense and passive voice, which can be confusing, especially with figure\ncaptions, e.g. Fig 3b: ‘A flowchart for the writing and reading process of English letters\nwas illustrated. The figure depicted the English alphabet alongside its corresponding\nbinary code table and provided a stepwise depiction of the encoding procedure for the\nletter ‘A’ within the TDON node.’\nResponse: Thank you for your suggestion. We have carefully proofread the entire text\nand tried to avoid using past tense and passive voice to make the article more fluent and\neasier to understand. We also revised the descriptions of the figure captions to make\nthem more clearly. All updates in the revised manuscript are highlighted in yellow\ncharacters.\nComment 15: Some examples of other language issues:\nline 24: ... different shaped DNA origami ...\nline 31: ... nanostructure-enabled ...\nline 43: ... which IS characterised ...\nline 56: ... different TO sequential storage ...\nline 58 ... obviate .. is unnecesarily uncommon word\nline 64: … the DNA PAINT technology\nline 72: …developed A DNA origami nanostructure-enabled\nlines 96–97: Benefitting to the programmability ...’\nline 146–147: ‘... covalently coupling data strands decorated SA, ...’\nline 156: ‘ After calculated the storage density ...’\nline 162: … The DON constituted a sophisticated design schema for data storage ->\nDON-based design scheme for data storage (if it is sophisticated or not is a question of\ntaste)\nline 164: … collaboratively forging a robust DNA nanostructure -> meaning of forging\nis mainly in the direction of ‘counterfeiting’, ‘pretending to be’\nline 178: … encode the clock wisely? line 180: ‘... English alphabets.’ - should be\n‘letters’\nlines 192-193: ‘... we turned to investigate the ability of the instructions to executive\ncommands.’\nLine 296: character instead of INDIVIDUAL RDON nodes line 296: probably should\nsay: ‘...instead of A SINGLE RDON node.’\nline 313: ‘Other from ...’\nline 344: ‘... were illustrated the workflow executed ...’\nResponse: We thank the reviewer for their meticulous attention to detail and for\npointing out these language issues. We have carefully reviewed the manuscript and\nimplemented the suggested corrections. Below is a point-by-point response to each\ncomment in the revised manuscript:\nPage 1, line 24: ‘...different shaped DNA origami...’ - Corrected to ‘...differently shaped\nDNA origami...’\nPage 2, line 31: ‘...nanostructure enabled...’ - Corrected to ‘...nanostructure-enabled...’\nPage 2, line 43–44: ‘...which characterised...’ - Corrected to ‘...which is characterized...’\nPage 3, line 59: ‘...different sequential storage...’ - Corrected to ‘...different to sequential\nstorage...’\nPage 3, line 61: ‘...obviate...’ - Replaced with ‘... thereby avoiding...’ for clarity.\nPage 3, line 67–68: ‘...the DNA-PAINT technology’ - Corrected to ‘...the DNA PAINT\ntechnology’\nPage 4, lines 100–101: ‘Benefitting to the programmability...’ - Corrected to\n‘Benefitting from the programmability...’\nPage 6, lines 157–158: ‘...covalently coupling data strands decorated SA...’ - Corrected\nto ‘...covalently coupling SA-decorated data strands...’\nPage 7, line 167: ‘After calculated the storage density...’ - Corrected to ‘After\ncalculating the storage density...’\nPage 7, line 174: ‘...The DON constituted a sophisticated design schema for data storage’\n- Revised to ‘DON-based design scheme for data storage’ to maintain a neutral tone.\nPage 7, line 176: ‘...collaboratively forging a robust DNA nanostructure’ - Replaced\n‘forging’ with ‘assembling’ to avoid unintended connotations.\nPage 8, line 188: ‘...encode the clock wisely?’ - Revised to ‘... encode in a clockwise\nspatial arrangement...’ for clarity.\nPage 8, line 190: ‘...English alphabets.’ - Corrected to ‘...English letters.’\nPage 8, lines 205–206: ‘...we turned to investigate the ability of the instructions to\nexecutive commands.’ - Corrected to ‘...we investigated the ability of the instructions\nto execute commands.’\nPage 14, line 315: ‘character instead of INDIVIDUAL RDON nodes’ - Corrected to\n‘...character instead of a single RDON node.’\nPage 14, line 336: ‘Other from...’ - Corrected to ‘Beyond monomeric RDON nodes...’\nPage 16, line 367–369: ‘...were illustrated the workflow executed...’ - Corrected to ‘The\nworkflow executed by the DONLDS system illustrated the processes of data insertion\nand deletion.’\nReviewer #4\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nResponse: We sincerely thank Reviewer #4 for their valuable contribution to the\nevaluation of our manuscript through Nature Communications’ innovative co-\nreviewing initiative. Your fresh perspective and rigorous assessment have significantly\nstrengthened this work. The collaborative insights from both reviewers have prompted\ncritical refinements throughout our study, particularly in optimizing structural designs,\ndeepening theoretical analysis, and clarifying technical implementations. We are\nhonored that our research benefited from your expertise during this developmental\nprocess and appreciate your dedication to advancing DNA nanotechnology. Your\ninvolvement has not only elevated this manuscript but also inspired our continued\nexploration of dynamic biomolecular storage systems.\nReferences\n1. Jiang, Y. et al. HS-AFM single-molecule structural biology uncovers basis of\ntransporter wanderlust kinetics. Nat. Struct. Mol. Biol. 31, 1286–1295 (2024).\n2. Biyani, M. et al. High-speed atomic force microscopy and 3D modeling reveal the\nstructural dynamics of ADAR1 complexes. Nature Commun. 16, 4757 (2025).\n3. Heath, G.R. & Scheuring, S. High-speed AFM height spectroscopy reveals µs-\ndynamics of unlabeled biomolecules. Nature Commun. 9, 4983 (2018).\n4. Kanaoka, Y. et al. AFM observation of protein translocation mediated by one unit\nof SecYEG-SecA complex. Nature Commun. 16, 225 (2025).\n5. Lv, H. et al. DNA-based programmable gate arrays for general-purpose DNA\ncomputing. Nature 622, 292–300 (2023).\n6. Bögels, B.W.A. et al. DNA storage in thermoresponsive microcapsules for\nrepeated random multiplexed data access. Nature Nanotech. 18, 912–921 (2023).\n7. Yang, L. et al. A spatially localized DNA linear classifier for cancer diagnosis.\nNature Commun. 15, 4583 (2024).\n8. Zhang, Q. et al. High-Speed Sequential DNA Computing Using a Solid-State DNA\nOrigami Register. ACS Cent. Sci. 10, 2285–2293 (2024).\n9. Kishi, J.Y. et al. SABER amplifies FISH: enhanced multiplexed imaging of RNA\nand DNA in cells and tissues. Nat. Methods 16, 533–544 (2019).\n10. Zhang, F. et al. Fluorescence Upconversion Microbarcodes for Multiplexed\nBiological Detection: Nucleic Acid Encoding. Adv. Mater. 23, 3739–3739 (2011).\n11. Narayanasamy, K.K., Rahm, J.V., Tourani, S. & Heilemann, M. Fast DNA-PAINT\nimaging using a deep neural network. Nature Commun. 13, 5047 (2022).\n12. Ghosh, A. et al. Decoding the molecular interplay of CD20 and therapeutic\nantibodies with fast volumetric nanoscopy. Science 387, eadq4510.\n13. Zaza, C. et al. Super-resolution imaging in whole cells and tissues via DNA-\nPAINT on a spinning disk confocal with optical photon reassignment. Nature\nCommun. 16, 4991 (2025)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "the authors have thoroughly addressed all the comments raised by this reviewer; thus, this reviewer recommends for publication.", "reviewer_2": "Thank you for the response. Instead of discussing openly (for instance by real comparison of writing/reading speeds to in silico archiving methods) the authors now discuss potential technology improvements that could make DNA origami archiving better. They make fair points, but they still shy away from being open about the real limitations.\nTo be clear: The error rates are far too large for any practical application, in particular when scaling to real world data sets. If this manuscript is published, it should be extremely open about these limitations. For example: Can the authors estimate what error rates one would expect when storing 1kB and 1MB of data? These are not really large amounts of data but already demonstrate the impracticability of the approach. What remains is a nice demonstration of DNA origami assembly. The authors have also provided the statistics I asked for. I leave it up to the editor to judge whether this is sufficient level of novelty for Nature Communications.", "reviewer_3": "The reviewers have taken the comments of the reviewers to heart and addressed them satisfactorily. These two reviewers think that the paper is now ready for publication.\nMinor comments:\n- in Fig. 6a they still have \"y\" instead of \"yes\" in two instances.\n- The authors went into detail in the reply how they would implement storage of 1Kbit of informatino and even included a table in the rebuttal (page 29) but we didn't find this in the article or the SI - maybe it would make sense to include it?", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Thank you for your evaluation and constructive suggestions on our manuscript. We are grateful for the opportunity to revise our work and address the concerns raised. Below, we provide a detailed point-by-point response to each commenter’s comments. All updates in the revised manuscript are highlighted in yellow characters.\nReviewer #1:\nthe authors have thoroughly addressed all the comments raised by this reviewer; thus,\nthis reviewer recommends for publication.\nResponse: We sincerely thank the reviewer for their positive evaluation and\nendorsement for publication. We are very glad to hear that our revisions have\nsatisfactorily addressed all comments. We greatly appreciate the time, expertise, and\nthoughtful feedback provided throughout the review process.\nReviewer #2:\nThank you for the response. Instead of discussing openly (for instance by real\ncomparison of writing/reading speeds to in silico archiving methods) the authors now\ndiscuss potential technology improvements that could make DNA origami archiving\nbetter. They make fair points, but they still shy away from being open about the real\nlimitations.\nTo be clear: The error rates are far too large for any practical application, in particular\nwhen scaling to real world data sets. If this manuscript is published, it should be\nextremely open about these limitations. For example: Can the authors estimate what\nerror rates one would expect when storing 1kB and 1MB of data? These are not really\nlarge amounts of data but already demonstrate the impracticability of the approach.\nWhat remains is a nice demonstration of DNA origami assembly. The authors have also\nprovided the statistics I asked for. I leave it up to the editor to judge whether this is\nsufficient level of novelty for Nature Communications.\nResponse: Thank you very much for once again reviewing our manuscript and\nproviding valuable feedback. We fully agree with your perspective that it is essential to\ncandidly and quantitatively discuss the core limitations of the current DNA Origami\nNanostructure-Linked Data Storage (DONLDS) system in terms of error rate and\nscalability. Your request for specific calculation processes to estimate the error rates\nwhen storing larger-scale data (such as 1 kB and 1 MB) is crucial for an objective\nassessment of the current state of this technology. Below is our detailed calculation and\nanalysis based on the current experimental data, and we have integrated this content\ninto the conclusion section of the paper.\nIn response, we have developed a refined computational model to better evaluate\nsystem scalability under varying redundancy conditions. This model employs a set of\nmathematical formulas that calculate the probability of successfully reading an entire\ndata block using an n-fold redundancy scheme combined with a majority voting\nmechanism, based on the experimentally determined raw bit error rate. The detailed\ncalculations and analysis, grounded in our current experimental data, have been\nintegrated into the conclusion section and supplementary of the paper.\n1. Single Logical Bit Success Rate (P )\nlogical\nThe probability that a minimum of mink minout of n physical copies are correct is given\nn\nby the cumulative binomial probability: P =∑ (n)qkpn-k\nlogical k\nk=kmin\n2. Full System Success Rate (P system)\nThe probability of correctly decoding all N independent logical bits in the data block is\nN\nthe product of their individual success probabilities: P =(P )\nsystem logical\n3. Variable Definitions\nVariable Description\np Raw bit error rate. The experimentally measured probability that a\nsingle physical bit is read incorrectly.\nq Raw bit accuracy. The probability that a single physical bit is read\ncorrectly. (q = 1 – p)\nn Redundancy factor. The number of physical copies stored for each\nsingle logical bit of data.\nk Majority vote threshold. The minimum number of correct physical\nmin\nn\ncopies required to correctly decode the logical bit. (k = [ ] + 1)\nmin\n8192 for 1 KB; 8,388,608 for 1 MB).\nP Single logical bit success Rate. The probability that a single logical\nlogical\nbit is correctly decoded from its n physical copies.\nP System success rate. The probability that the entire data block of N\nsystem\nlogical bits is recovered without error.\nThe description of computational model has been added in Supplementary Section 1.\nmaterials and methods. (Page 5)\nDON Raw Bit Error Redundancy Factor Single Logical Bit Success\nTypes Rate (p) (n) Rate (P )\nlogical\nTDON 1.44% 5 99.97%\nCDON 1.37% 5 99.98%\nRDON 1.11% 5 99.99%\nSupplementary Table 4 | The logical bit success rates of three DON types (TDON,\nCDON, and RDON) under the condition of a fixed redundancy factor n=5. As shown\nin the table, the raw bit error rate (p) varies among different DON types: TDON has a\np of 1.44%, CDON has 1.37%, and RDON has 1.11%. Correspondingly, their single\nlogical bit success rates (P ) are 99.97%, 99.98%, and 99.99%, respectively. It can\nlogical\nbe observed that with the decrease in the raw bit error rate, the logical bit success rate\nshows a gradually increasing trend. This indicates that under the same redundancy\nmechanism (with n=5), a lower raw bit error rate contributes to a higher reliability of\nlogical bit transmission.\nThe Supplementary Table 4 have been added in the revised Supplementary. (Page 47)\nSupplementary Fig. 40 | The system success rate under different redundancy factors.\nSystem-level recovery probability with multi-copy redundancy (p = 0.0131, the average\nraw bit error rate of DON). 1 KB success rises sharply from ~0% at n≤6 to near 100%\nfor n≥10. 1 MB success stays ~0% until n≥8, then surges to near 100% for n≥12. Larger\ndata (1 MB) needs higher n for high reliability, with both showing rapid success rate\ngrowth beyond a threshold n. Source data are provided as a Source Data file.\nThe images have been placed in Figure 40 of the revised Supplementary. (Page 45)\nWe have clarified this in the revised manuscript (Page 18-19, Lines 443–448): “To\naccurately predict the storage success rate for larger-scale data, we use a refined\ncomputational model. This model is described in detail in the supplementary methods\nsection, which includes parameterized mathematical formulas that systematically\ncalculate the data storage success rate under corresponding conditions by taking the raw\nbit error rate as an input variable (Supplementary Table 4 and Fig. 40).”\nAlthough the raw bit error rate is relatively high, ranging from 1.11% to 1.44%,\nany desired level of reliability can theoretically be achieved through redundancy and\nerror-correcting codes. However, the required redundancy increases dramatically with\nthe amount of data. For small data volumes (e.g., 1 kB), a relatively low redundancy\nfactor is sufficient to achieve high reliability. By adopting 10-fold redundant encoding\nand a majority voting mechanism, we improved the system-level correctness rate for\nreading 1 kB of data from nearly zero to over 99.9%. This result demonstrates that,\ndespite the high raw error rate, our DONLDS approach can achieve practical data\nreliability through appropriate system-level design, including redundancy and error\ncorrection.\nFor larger data volumes (e.g., 1 MB), more sophisticated error-correcting coding\nschemes (such as concatenated codes, LDPC, etc.) and higher redundancy are required.\nThis represents an important direction for our future work.\nIn response, we have added the following passage to the conclusions chapter of\nthe revised manuscript (Page 23, Lines 546–560): “Although the raw bit error rate is\nrelatively high, ranging from 1.11% to 1.44%, any desired level of reliability can\ntheoretically be achieved through redundancy and error-correcting codes (ECC).\nHowever, the required redundancy increases substantially with data volume. For\nexample, using a 10-fold redundant encoding scheme with majority voting, we\nimproved the system-level correctness for reading 1 kB of data from nearly zero to over\n99.9%, demonstrating that practical data reliability can be attained in DONLDS through\nappropriate system-level design. For larger data volumes, such as 1 MB, more\nsophisticated ECC schemes (e.g., Reed–Solomon) and higher redundancy ratios would\nbe required. Therefore, before DONLDS-based storage systems can be practically\ndeployed, they must incorporate such robust ECC and redundancy schemes. At this\nstage, DONLDS should be regarded as a proof-of-concept platform for exploring\ndynamic data operations (e.g., insertion and deletion) in molecular storage systems. Its\nscalability ultimately depends on synergistic breakthroughs in coding theory, materials\nscience, and readout technologies.”\nOnce again, we sincerely thank you for your valuable time and highly insightful\ncomments, which have greatly enhanced the rigor of our manuscript.\nReviewer #3:\nThe reviewers have taken the comments of the reviewers to heart and addressed them\nsatisfactorily. These two reviewers think that the paper is now ready for publication.\nResponse: We are pleased to hear that the reviewers found our responses satisfactory\nand consider the manuscript ready for publication. We greatly appreciate your\nconstructive feedback throughout the review process, which has significantly\nstrengthened the paper. Thank you for facilitating this productive dialogue.\nMinor comments:\n1. in Fig. 6a they still have “y” instead of “yes” in two instances.\nResponse: We thank the reviewers for pointing out the omission. We have replaced the\n“y” representing “yes” in Fig. 6a.\nFig. 6 a, A flowchart for the insertion of DON nodes.\nThe images have been replaced in revised manuscript Fig. 6a. (Page 19, Line 450)\n2. The authors went into detail in the reply how they would implement storage of\n1Kbit of information and even included a table in the rebuttal (page 29) but we didn’t\nfind this in the article or the SI - maybe it would make sense to include it?\nResponse: We appreciate you pointing out that it would be beneficial to include this\ninformation in the manuscript itself rather than just in the rebuttal. We have followed\nyour advice. The detailed explanation and the corresponding table from our rebuttal\nhave now been incorporated into the Supplementary Information in page 46.\nWe have clarified this in the revised manuscript (Page 5, Lines 123–125): “For\nexample, to store 1Kbit of data, we divide the data into 10 layers, and each layer\nrequires 100-144 types of pointer strands and operation strands (Supplementary Table\n1).”\nSpecies Storage type Capacity/node Layer Storage P O\nt t\nTDON English letters 8 Bit 10 1Kbit 144 144\nRDON Chinese characters 12 Bit 10 1Kbit 100 100\nCDON Arabic numerals 8 Bit 10 1Kbit 144 144\nNote: Pointer strands types (P); Operation strands types (O)\nt t\nSupplementary Table 1 | The relationship between DNA strand usage and storage\ncapacity. All targeting 1Kbit data via 10-layer partitioning: TDON/CDON (8 Bit/node,\nfor English letters/Arabic numerals) require 144 types of pointer (P) and operation (O)\nt t\nstrands each, while RDON (12 Bit/node, for Chinese characters) needs 100 types.\nThe Supplementary Table 1 have been added in the revised Supplementary. (Page 46)\nReviewer #4:\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports.\nThis is part of the Nature Communications initiative to facilitate training in peer review\nand to provide appropriate recognition for Early Career Researchers who co-review\nmanuscripts.\nResponse:We thank the reviewer for their insightful comments and also extend our\nappreciation to Nature Communications for facilitating this collaborative review\nprocess, which provides meaningful opportunities for early-career researchers to\nparticipate in peer review.\nWe have carefully considered all the feedback provided by the reviewers and have\naddressed each of the points in our revised manuscript. Every suggestion has been\nincorporated to enhance the scientific rigor and clarity of the paper."}, {"round": 3, "reviewer_comments": {"reviewer_2": "Thank you for the clarification. It really helps to put the work into context. I am happy with the publication in the current form."}, "author_response": ""}]

Decision letter