Storing Images in DNA via base128 Encoding.

Current DNA storage schemes lack flexibility and consistency in processing highly redundant and correlated image data, resulting in low sequence stability and image reconstruction rates. Therefore, according to the characteristics of image storage, this paper proposes storing images in DNA via base128 encoding (DNA-base128). In the data writing stage, data segmentation and probability statistics are carried out, and then, the data block frequency and constraint encoding set are associated with achieving encoding. When the image needs to be recovered, DNA-base128 completes internal error correction by threshold setting and drift comparison. Compared with representative work, the DNA-base128 encoding results show that the undesired motifs were reduced by 71.2-90.7% and that the local guanine-cytosine content variance was reduced by 3 times, indicating that DNA-base128 can store images more stably. In addition, the structural similarity index (SSIM) and multiscale structural similarity (MS-SSIM) of image reconstruction using DNA-base128 were improved by 19-102 and 6.6-20.3%, respectively. In summary, DNA-base128 provides image encoding with internal error correction and provides a potential solution for DNA image storage. The data and code are available at the GitHub repository: https://github.com/123456wk/DNA_base128.

Rhizopus oryzae causes the leaf rot disease of Epimedium sagittatum in Guizhou, China.

Epimedium sagittatum is a collective term for herbaceous plants belonging to the family Berberidaceae. Their dried leaves and stems have significant therapeutic effects on tumor inhibition, hypertension control, and coronary heart disease (Ke et al. 2023; Zhao et al. 2019). In 2021 and 2022, plants with similar leaf rot symptoms ranging from 30% to 55% was observed on E. sagittatum in Congjiang County, Guizhou province. The initial symptoms of the disease manifest locally on the leaf, with yellowing on the surface edge of the affected tissue, browning in the middle part, and brown-white discoloration in the innermost part (Supplementary Figure S1B). As the disease progresses, the entire infected leaf gradually softens, while the veins remain intact (Supplementary Figure S1C). Ultimately, the leaf withers and dehisces. The nine samples with typical symptoms were collected from Congjiang County, Guizhou province (26.598°N, 106.707°E). Twenty-seven fungi were isolated, including ten isolates of Rhizopus and seventeen isolates of seven other genera. On isolate YYH-CJ-17 many sporangia were formed and turned to a brown-gray to black color on potato dextrose agar medium (PDA) after culturing 5 days under dark at 25 ℃ (Supplementary Figure S2A and S2B). The branches of mycelium were finger-shaped or root-shaped. The sporangium was spherical or nearly spherical, 60-250 µm in diameter, and sporangiospores were elliptical or spherical and 4-8 µm in diameter. The obtained 547 bp ITS fragment (accession OR225970) and 1231 bp EF-1α region (accession OR242258) from isolate YYH-CJ-17 were compared with NR database using the BLAST tool provided by NCBI, which revealed more than 99.5% identity (query cover more than 98%) with the sequences of ITS (accessions MF522822.1) and EF-1α (accession AB281541.1) of Rhizopus oryzae Went & H.C. Prinsen Geerlings (Gao et al. 2022; Zhang et al. 2022). The phylogenetic tree constructed with the ITS and EF-1α gene sequences demonstrates that strain YYH-CJ-17 clusters with R. oryzae in the same branch and the bootstrap value was greater than 99% (Supplementary Figure S3). Based on the morphological characteristics and ITS and EF-1a sequences, the isolate YYH-CJ-17 is identified as R. oryzae. Pathogenicity tests were performed on detached healthy leaves and living plants of E. sagittatum. Healthy leaves of E. sagittatum were subjected to inoculation with isolate YYH-CJ-17 with 5 × 105 CFU mL-1 concentration in sterile culture dishes. The progression of the disease was marked by the gradual softening of the infected leaves and the expansion of the lesions, which ultimately produced black-brown sporangium (Supplementary Figure S4A). Furthermore, the E. sagittatum living plants were sprayed with 5 × 105 CFU mL-1 conidial suspension of isolate YYH-CJ-17, with ddH2O as a negative control, and then were cultivated at 25℃ and 90% humidity for 21 days in the greenhouse. This assay found that the E. sagittatum leaves treated with isolate YYH-CJ-17 exhibited the same symptoms observed on plants in fields (Supplementary Figure S4B). The fungus re-isolated from the inoculated leaves were identified as R. oryzae by ITS sequencing and were blasted with NR database, which highest matched with the sequence of ITS (accessions MF522822.1) mentioned above, thus fulfilling Koch's postulates. R. oryzae has been identified as a causative agent of a diverse array of host diseases, including leaf mildew of tobacco, fruit rot of yellow oleander and pears, and soft rot of bananas (Farooq et al. 2017; Khokhar et al. 2019; Kwon et al. 2012; Pan et al. 2021). To the best of our knowledge, this is the first report of leaf rot on E. sagittatum caused by R. oryzae in China, which will provide clear prevention and management target for the leaf rot disease of E. sagittatum.

Study on DNA Storage Encoding Based IAOA under Innovation Constraints.

With the informationization of social processes, the amount of related data has greatly increased, making traditional storage media unable to meet the current requirements for data storage. Due to its advantages of a high storage capacity and persistence, deoxyribonucleic acid (DNA) has been considered the most prospective storage media to solve the data storage problem. Synthesis is an important process for DNA storage, and low-quality DNA coding can increase errors during sequencing, which can affect the storage efficiency. To reduce errors caused by the poor stability of DNA sequences during storage, this paper proposes a method that uses the double-matching and error-pairing constraints to improve the quality of the DNA coding set. First, the double-matching and error-pairing constraints are defined to solve problems of sequences with self-complementary reactions in the solution that are prone to mismatch at the 3' end. In addition, two strategies are introduced in the arithmetic optimization algorithm, including a random perturbation of the elementary function and a double adaptive weighting strategy. An improved arithmetic optimization algorithm (IAOA) is proposed to construct DNA coding sets. The experimental results of the IAOA on 13 benchmark functions show a significant improvement in its exploration and development capabilities over the existing algorithms. Moreover, the IAOA is used in the DNA encoding design under both traditional and new constraints. The DNA coding sets are tested to estimate their quality regarding the number of hairpins and melting temperature. The DNA storage coding sets constructed in this study are improved by 77.7% at the lower boundary compared to existing algorithms. The DNA sequences in the storage sets show a reduction of 9.7-84.1% in the melting temperature variance, and the hairpin structure ratio is reduced by 2.1-80%. The results indicate that the stability of the DNA coding sets is improved under the two proposed constraints compared to traditional constraints.

A nicking enzyme-assisted allosteric strategy for self-resetting DNA switching circuits.

The self-regulation of biochemical reaction networks is crucial for maintaining balance, stability, and adaptability within biological systems. DNA switching circuits, serving as basic units, play essential roles in regulating pathways, facilitating signal transduction, and processing biochemical reaction networks. However, the non-reusability of DNA switching circuits hinders its application in current complex information processing. Herein, we proposed a nicking enzyme-assisted allosteric strategy for constructing self-resetting DNA switching circuits to realize complex information processing. This strategy utilizes the unique cleavage ability of the nicking enzyme to achieve the automatic restoration of states. Based on this strategy, we implemented a self-resetting DNA switch. By leveraging the reusability of the DNA switch, we constructed a DNA switching circuit with selective activation characteristics and further extended its functionality to include fan-out and fan-in processes by expanding the number of functional modules and connection modes. Furthermore, we demonstrated the complex information processing capabilities of these switching circuits by integrating recognition, translation, and decision functional modules, which could analyze and transmit multiple input signals and realize parallel logic operations. This strategy simplifies the design of switching circuits and promotes the future development of biosensing, molecular computing, and nanomachines.

Study on auxiliary operation control of machine learning in multiobjective complex drainage system.

Recently, urban waterlogging prevention and treatment of black-odorous rivers have become a social concern and the upgradation of drainage system and the development of river runoff pollution control projects have accelerated. The use of deep tunnels to upgrade old drainage systems and achieve pollution control-related engineering designs has complicated the drainage system operation control. The traditional operation control mainly relies on human experience or model simulation. This study provides a perspective of machine learning for controlling the operation of the drainage system and exploring whether the operation suggestions regarding facilities in this system can be given in real time while relying only on real-time data and avoiding the complex model simulation process. Herein, five drainage systems were used as examples: the initial water level of a pipeline, key point water level flow, pump station front pool water level, and most unfavorable point water level were selected as relevant variables and four machine-learning discrimination methods were used for to analyze the weir-lowering operation of a deep tunnel. This study found that the average error rate of the linear discrimination method was <10%, thereby exhibiting satisfactory performance. This study provides insights for improving the operation of complex drainage systems.

Design of DNA Storage Coding with Enhanced Constraints.

Traditional storage media have been gradually unable to meet the needs of data storage around the world, and one solution to this problem is DNA storage. However, it is easy to make errors in the subsequent sequencing reading process of DNA storage coding. To reduces error rates, a method to enhance the robustness of the DNA storage coding set is proposed. Firstly, to reduce the likelihood of secondary structure in DNA coding sets, a repeat tandem sequence constraint is proposed. An improved DTW distance constraint is proposed to address the issue that the traditional distance constraint cannot accurately evaluate non-specific hybridization between DNA sequences. Secondly, an algorithm that combines random opposition-based learning and eddy jump strategy with Aquila Optimizer (AO) is proposed in this paper, which is called ROEAO. Finally, the ROEAO algorithm is used to construct the coding sets with traditional constraints and enhanced constraints, respectively. The quality of the two coding sets is evaluated by the test of the number of issuing card structures and the temperature stability of melting; the data show that the coding set constructed with ROEAO under enhanced constraints can obtain a larger lower bound while improving the coding quality.

An Efficient Improved Greedy Harris Hawks Optimizer and Its Application to Feature Selection.

To overcome the lack of flexibility of Harris Hawks Optimization (HHO) in switching between exploration and exploitation, and the low efficiency of its exploitation phase, an efficient improved greedy Harris Hawks Optimizer (IGHHO) is proposed and applied to the feature selection (FS) problem. IGHHO uses a new transformation strategy that enables flexible switching between search and development, enabling it to jump out of local optima. We replace the original HHO exploitation process with improved differential perturbation and a greedy strategy to improve its global search capability. We tested it in experiments against seven algorithms using single-peaked, multi-peaked, hybrid, and composite CEC2017 benchmark functions, and IGHHO outperformed them on optimization problems with different feature functions. We propose new objective functions for the problem of data imbalance in FS and apply IGHHO to it. IGHHO outperformed comparison algorithms in terms of classification accuracy and feature subset length. The results show that IGHHO applies not only to global optimization of different feature functions but also to practical optimization problems.

[Screening of zearalenone-degrading bacteria and analysis of degradation conditions].

Zearalenone(ZEN) is a mycotoxin produced by Fusarium, possessing estrogen-like effects, carcinogenicity, and multiple toxicities. To seek more efficient and practical agents for biological detoxification and broaden their application, this study isolated 194 bacterial strains from the moldy tuberous root of Pseudostellaria heterophylla, which were co-cultured with ZEN. An efficient ZEN-degrading strain H4-3-C1 was screened out by HPLC and identified as Acinetobacter calcoaceticus by morphological observation and molecular identification. The effects of culture medium, inoculation dose, culture time, pH, and temperature on the degradation of ZEN by H4-3-C1 strain were investigated. The mechanism of ZEN degradation and the degrading effect in Coicis Semen were discussed. The degradation rate of 5 µg·mL~(-1) ZEN by H4-3-C1 strain was 85.77% in the LB medium(pH 6) at 28 ℃/180 r·min~(-1) for 24 h with the inoculation dose of 1%. The degradation rate of ZEN in the supernatant of strain culture was higher than that in the intracellular fluid and thalli. The strain was inferred to secret extracellular enzymes to degrade ZEN. In addition, the H4-3-C1 strain could also degrade ZEN in Coicis Semen. If the initial content of ZEN in Coicis Semen was reduced from 90 µg·g~(-1) to 40.68 µg·g~(-1), the degradation rate could reach 54.80%. This study is expected to provide a new strain and application technology for the biological detoxification of ZEN in food processing products and Chinese medicinal materials.

[Isolation of Fusarium and identification of its toxins from tuberous root of Pseudostellaria heterophylla].

Fusarium is the major pathogen of root rot of Pseudostellaria heterophylla. This study aims to explain the possible distribution of Fusarium species and the contamination of its toxin-chemotypes in tuberous root of P. heterophylla. A total of 89 strains of fungi were isolated from the tuberous root of P. heterophylla. Among them, 29 strains were identified as Fusarium by ITS2 sequence, accounting for 32.5%. They were identified as five species of F. avenaceum, F. tricinctum, F. fujikuroi, F. oxysporum, and F. graminearum based on ß-Tubulin and EF-1α genes. LC-MS/MS detected 18, 1, and 5 strains able to produce ZEN, DON, and T2, which accounted for 62.1%, 3.4%, and 17.2%, respectively. Strain JK3-3 can produce ZEN, DON, and T2, while strains BH1-4-1, BH6-5, and BH16-2 can produce ZEN and T2. PCR detected six key synthase genes of Tri1, Tri7, Tri8, Tri13, PKS14, and PKS13 in strain JK3-3, which synthesized three toxins of ZEN, DON, and T2. Four key synthase genes of Tri8, Tri13, PKS14, and PKS13 were detected in strains BH1-4-1, BH6-5, and BH16-2, which were responsible for the synthesis of ZEN and T2. The results showed that the key genes of toxin biosynthesis were highly correlated with the toxins produced by Fusarium, and the biosynthesis of toxin was strictly controlled by the genetic information of the strain. This study provides a data basis for the targeted prevention and control of exo-genous mycotoxins in P. heterophylla and a possibility for the development of PCR for rapid detection of toxin contamination.

A Dynamic DNA Color Image Encryption Method Based on SHA-512.

This paper presents a dynamic deoxyribonucleic acid (DNA) image encryption based on Secure Hash Algorithm-512 (SHA-512), having the structure of two rounds of permutation-diffusion, by employing two chaotic systems, dynamic DNA coding, DNA sequencing operations, and conditional shifting. We employed the SHA-512 algorithm to generate a 512-bit hash value and later utilized this value with the natural DNA sequence to calculate the initial values for the chaotic systems and the eight intermittent parameters. We implemented a two-dimensional rectangular transform (2D-RT) on the permutation. We used four-wing chaotic systems and Lorentz systems to generate chaotic sequences and recombined three channel matrices and chaotic matrices with intermittent parameters. We calculated hamming distances of DNA matrices, updated the initial values of two chaotic systems, and generated the corresponding chaotic matrices to complete the diffusion operation. After diffusion, we decoded and decomposed the DNA matrices, and then scrambled and merged these matrices into an encrypted image. According to experiments, the encryption method in this paper not only was able to withstand statistical attacks, plaintext attacks, brute-force attacks, and a host of other attacks, but also could reduce the complexity of the algorithm because it adopted DNA sequencing operations that were different from traditional DNA sequencing operations.

Correcting Errors in Image Encryption Based on DNA Coding.

As a primary method, image encryption is widely used to protect the security of image information. In recent years, image encryption pays attention to the combination with DNA computing. In this work, we propose a novel method to correct errors in image encryption, which results from the uncertainty of DNA computing. DNA coding is the key step for DNA computing that could decrease the similarity of DNA sequences in DNA computing as well as correct errors from the process of image encryption and decryption. The experimental results show our method could be used to correct errors in image encryption based on DNA coding.

[Effect of SLC7A5 on the proliferation of tumor cells and its relationship with transforming growth factor-ß1 signal pathway].

OBJECTIVE: To explore the biological effects of amino acid transporter gene SLC7A5 (solute carrier family 7, member 5) on tumor cells and the regulatory mechanism at transcriptional level.
 Methods: The expression of SLC7A5 was examined in human normal tissues and corresponding tumor tissues by Gene Expression Omnibus (GEO) database. The recombinant plasmid of SLC7A5 gene was constructed, and the effect of the SLC7A5 gene on tumor cell proliferation was investigated by methylthiazolyldiphenyl-tetrazolium bromide (MTT) and flow cytometry. SLC7A5 gene promoter and transcription factor binding sites were predicted through bioinformatics analysis, and the gene promoter recombinant plasmid was constructed. Then the dual luciferase reporter gene assay and reverse transcription polymerase chain reaction (RT-PCR) were used to explore the regulation of transforming growth factor-ß1 (TGF-ß1) signal on SLC7A5 gene expression.
 Results: The GEO database analysis showed that the distribution of SLC7A5 was tissue specific, and its expression level was significantly higher in the tumor tissues than that in the corresponding normal tissues. The results of MTT and flow cytometry showed that SLC7A5 could promote cell proliferation. Results from the promoter analysis, reporter gene assay and RT-PCR confirmed that TGF-ß1 could up-regulate the activity of SLC7A5 promoter and promote the expression of the SLC7A5 gene.
 Conclusion: SLC7A5 gene plays a role in promoting tumor development, which is regulated by the TGF-ß1 signaling pathway.

Discrete Salp Swarm Algorithm for symmetric traveling salesman problem.

In the Salp Swarm Algorithm (SSA), the update mechanism is inspired by the unique chain movement of the salp swarm. Numerous versions of SSA were already put forward to deal with various optimization problems, but there are very few discrete versions among them. d-opt is improved based on the 2-opt algorithm: a decreasing factor d is introduced to control the range of neighborhood search; TPALS are modified by Problem Aware Local Search (PALS) based on the characteristics of Travelling Salesman Problem (TSP); The second leader mechanism increases the randomness of the algorithm and avoids falling into the local optimal solution to a certain extent. We also select six classical crossover operators to experiment and select Subtour Exchange Crossover (SEC) and the above three mechanisms to integrate them into the SSA algorithm framework to form Discrete Salp Swarm Algorithm (DSSA). In addition, DSSA was tested on 23 known TSP instances to verify its performance. Comparative simulation studies with other advanced algorithms are conducted and from the results, it is observed that DSSA satisfactorily solves TSP.

GeSeNet: A General Semantic-Guided Network With Couple Mask Ensemble for Medical Image Fusion.

At present, multimodal medical image fusion technology has become an essential means for researchers and doctors to predict diseases and study pathology. Nevertheless, how to reserve more unique features from different modal source images on the premise of ensuring time efficiency is a tricky problem. To handle this issue, we propose a flexible semantic-guided architecture with a mask-optimized framework in an end-to-end manner, termed as GeSeNet. Specifically, a region mask module is devised to deepen the learning of important information while pruning redundant computation for reducing the runtime. An edge enhancement module and a global refinement module are presented to modify the extracted features for boosting the edge textures and adjusting overall visual performance. In addition, we introduce a semantic module that is cascaded with the proposed fusion network to deliver semantic information into our generated results. Sufficient qualitative and quantitative comparative experiments (i.e., MRI-CT, MRI-PET, and MRI-SPECT) are deployed between our proposed method and ten state-of-the-art methods, which shows our generated images lead the way. Moreover, we also conduct operational efficiency comparisons and ablation experiments to prove that our proposed method can perform excellently in the field of multimodal medical image fusion. The code is available at https://github.com/lok-18/GeSeNet.

Programming DNA Reaction Networks Using Allosteric DNA Hairpins.

The construction of DNA reaction networks with complex functions using various methods has been an important research topic in recent years. Whether the DNA reaction network can perform complex tasks and be recycled directly affects the performance of the reaction network. Therefore, it is very important to design and implement a DNA reaction network capable of multiple tasks and reversible regulation. In this paper, the hairpin allosteric method was used to complete the assembly task of different functional nucleic acids. In addition, information conversion of the network was realized. In this network, multiple hairpins were assembled into nucleic acid structures with different functions to achieve different output information through the cyclic use of trigger strands. A method of single-input dual-output information conversion was proposed. Finally, the network with signal amplification and reversible regulation was constructed. In this study, the reversible regulation of different functional nucleic acids in the same network was realized, which shows the potential of this network in terms of programmability and provides new ideas for constructing complex and multifunctional DNA reaction networks.

Reconfigurable DNA triplex structure for pH responsive logic gates.

The DNA triplex is a special DNA structure often used as a logic gate substrate due to its high stability, programmability, and pH responsiveness. However, multiple triplex structures with different C-G-C+ proportions must be introduced into existing triplex logic gates due to the numerous logic calculations involved. This requirement complicates circuit design and results in many reaction by-products, greatly restricting the construction of large-scale logic circuits. Thus, we designed a new reconfigurable DNA triplex structure (RDTS) and constructed the pH-responsive logic gates through its conformational change that uses two types of logic calculations, 'AND' and 'OR'. The use of these logic calculations necessitates fewer substrates, further enhancing the extensibility of the logic circuit. This result is expected to promote the development of the triplex in molecular computing and facilitate the completion of large-scale computing networks.

Volatiles from Pseudomonas palleroniana Strain B-BH16-1 Suppress Aflatoxin Production and Growth of Aspergillus flavus on Coix lacryma-jobi during Storage.

Semen coicis is not only a traditional Chinese medicine (TCM), but also a typical food in China, with significant medical and healthcare value. Because semen coicis is rich in starch and oil, it can be easily contaminated with Aspergillus flavus and its aflatoxins (AFs). Preventing and controlling the contamination of semen coicis with Aspergillus flavus and its aflatoxins is vital to ensuring its safety as a drug and as a food. In this study, the endosphere bacteria Pseudomonas palleroniana strain B-BH16-1 produced volatiles that strongly inhibited the mycelial growth and spore formation activity of A. flavus. Gas chromatography-mass spectrometry profiling revealed three volatiles emitted from B-BH16-1, of which 1-undecene was the most abundant. We obtained authentic reference standards for these three volatiles; these significantly reduced mycelial growth and sporulation in Aspergillus, with dimethyl disulfide showing the most robust inhibitory activity. Strain B-BH16-1 was able to completely inhibit the biosynthesis of aflatoxins in semen coicis samples during storage by emitting volatile bioactive components. The microscope revealed severely damaged mycelia and a complete lack of sporulation. This newly identified plant endophyte bacterium was able to strongly inhibit the sporulation and growth of Aspergillus and the synthesis of associated mycotoxins, thus not only providing valuable information regarding an efficient potential strategy for the prevention of A. flavus contamination in TCM and food, but potentially also serving as a reference in the control of toxic fungi.

Biomolecule-Driven Two-Factor Authentication Strategy for Access Control of Molecular Devices.

The rise of DNA nanotechnology is promoting the development of molecular security devices and marking an essential change in information security technology, to one that can resist the threats resulting from the increase in computing power, brute force attempts, and quantum computing. However, developing a secure and reliable access control strategy to guarantee the confidentiality of molecular security devices is still a challenge. Here, a biomolecule-driven two-factor authentication strategy for access control of molecular devices is developed. Importantly, the two-factor is realized by applying the specificity and nicking properties of the nicking enzyme and the programmable design of the DNA sequence, endowing it with the characteristic of a one-time password. To demonstrate the feasibility of this strategy, an access control module is designed and integrated to further construct a role-based molecular access control device. By constructing a command library composed of three commands (Ca, Cb, Ca and Cb), the authorized access of three roles in the molecular device is realized, in which the command Ca corresponds to the authorization of role A, Cb corresponds to the authorization of role B, and Ca and Cb corresponds to the authorization of role C. In this way, when users access the device, they not only need the correct factor but also need to apply for role authorization in advance to obtain secret information. This strategy provides a highly robust method for the research on access control of molecular devices and lays the foundation for research on the next generation of information security.

An enhanced whale optimization algorithm for DNA storage encoding.

Metaheuristic algorithms have the drawback that local optimal solutions are prone to precocious convergence. In order to overcome the disadvantages of the whale optimization algorithm, we propose an improved selective opposition whale optimization algorithm (ISOWOA) in this paper. Firstly, the enhanced quasi-opposition learning (EQOBL) is applied to selectively update the position of the predator, calculate the fitness of the population before and after, and retain optimal individuals as the food source position; Secondly, an improved time-varying update strategy for inertia weight predator position is proposed, and the position update of the food source is completed by this strategy. The performance of the algorithm is analyzed by 23 benchmark functions of CEC 2005 and 15 benchmark functions of CEC 2015 in various dimensions. The superior results are further shown by Wilcoxon's rank sum test and Friedman's nonparametric rank test. Finally, its applicability is demonstrated through applications to the field of biological computing. In this paper, our aim is to achieve access to DNA files and designs high-quantity DNA code sets by ISOWOA. The experimental results show that the lower bounds of the multi-constraint storage coding sets implemented in this paper equals or surpasses that of previous optimal constructions. The data show that the amount of the DNA storage cods filtered by ISOWOA increased 2-18%, which demonstrates the algorithm's reliability in practical optimization tasks.

DNA Matrix Operation Based on the Mechanism of the DNAzyme Binding to Auxiliary Strands to Cleave the Substrate.

Numerical computation is a focus of DNA computing, and matrix operations are among the most basic and frequently used operations in numerical computation. As an important computing tool, matrix operations are often used to deal with intensive computing tasks. During calculation, the speed and accuracy of matrix operations directly affect the performance of the entire computing system. Therefore, it is important to find a way to perform matrix calculations that can ensure the speed of calculations and improve the accuracy. This paper proposes a DNA matrix operation method based on the mechanism of the DNAzyme binding to auxiliary strands to cleave the substrate. In this mechanism, the DNAzyme binding substrate requires the connection of two auxiliary strands. Without any of the two auxiliary strands, the DNAzyme does not cleave the substrate. Based on this mechanism, the multiplication operation of two matrices is realized; the two types of auxiliary strands are used as elements of the two matrices, to participate in the operation, and then are combined with the DNAzyme to cut the substrate and output the result of the matrix operation. This research provides a new method of matrix operations and provides ideas for more complex computing systems.