DNA Machine Research Articles

Bisphenol a monitoring by commercial pregnancy test strips transformed by DNA walking machine

Frequently occurred food contamination issues bring about a tremendous global demand for point-of-care testing (POCT) devices. Pregnancy test strip (PTS) retains the highest POCT market share and a low cost of $0.10 per test, but challenged by limited analytical sensitivity and non-autonomous signal transduction for drink contaminant monitoring. Herein, we developed a DNA walking machine-assisted commercial PTS method for on-site bisphenol A (BPA) analysis in drink. DNAzyme was operated as the efficient autonomous catalytic walker chain to drive the DNA machine for the amplified signal output of BPA in drink samples. A detection limit of 16.8 pg/mL was obtained, which is three orders of magnitude lower than the regulatory limit of European Union (Commission Regulation (EU) 2020/1245). The POCT strategy constructed in this work has the characteristics of low cost, convenient operation and high analytical sensitivity, represents an attractive option for biosensing and on-site drink safety monitoring.

A DNA machine-based magnetic resonance imaging nanoprobe for in vivo microRNA detection

In situ monitoring microRNA (miRNA) expression in vivo holds immense potential for directly visualizing the occurrence and progression of tumors. However, the significant barrier to developing a probe that can overcome the low abundance of miRNAs while providing an output signal with unlimited tissue penetration depth remains formidable. In this study, we developed a DNA machine-based magnetic resonance imaging nanoprobe (MRINP) for amplified detection of miR-21 in vivo. The MRINP was constructed with superparamagnetic Fe3O4 nanoparticles (NPs), paramagnetic Gd-DOTA complexes, and miR-21-activated DNA machines; the DNA machine was composed of hairpin DNAzyme (HD) strands serving as the DNAzyme walker and hairpin substrate (HS) strands serving as the track. Once uptake into tumor cells, the intracellular miR-21 specifically recognized and hybridized with the HD strand, restoring the activity of DNAzyme. Subsequently, the DNAzyme walker autonomously traveled on the surface of MRINP, and each step movement of the DNAzyme walker resulted in the cleavage of its substrate strands and the ensued release of the Gd-DOTA complex-labeled oligonucleotides, turning on the T1 signal of Gd-DOTA complexes for in situ imaging of miR-21 in tumor-bearing mice. This strategy would offer a promising approach for mapping tumor-specific biomarkers in vivo with unlimited penetration depth.

Enhancing Early Cancer Detection: An Investigation of DNA Sequences and Machine Learning

The study aimed to address the global challenge of cancer-related fatalities by investigating the feasibility of identifying or predicting the early-stage presence of three distinct forms of cancers, colon, thyroid and urothelial carcinoma, via the analysis of raw DNA sequences. The data, sourced from the NCBI database, underwent a series of pre-processing techniques, including kmer analysis, under-sampling and count vectorization. Subsequently, machine learning algorithms, including logistic regression and multinomial Naive Bayes, were implemented on the pre-processed data with logistic regression demonstrating superior accuracy of 80.10% with calibration and 78.54% without calibration. To enhance the model's extrapolative capabilities, the logistic regression model was further calibrated utilizing the sigmoid method. The final model was deployed through the utilization of the open-source streamlit package.

Spectral Fingerprinting Coupled Machine Learning: An Optimized Tool for Cellular Phenotype Identification

Spectral fingerprinting has emerged as a powerful tool for unraveling intricate interactions between the intracellular environment and nanomaterials. This study leverages spectral fingerprinting to deepen our comprehension of the interplay between macrophages and nanotubes, utilizing their Near Infrared fluorescence to discern cellular characteristics. This study employs Raman microscopy to showcase significant differences in defect ratio and intracellular processing of nanotubes, among macrophage phenotypes. The near infrared features of DNA-SWCNTs serve as distinctive markers for identifying different macrophage phenotypes. Here we use a support vector machine learning model to accurately identify M1 and M2 macrophages, achieving an impressive accuracy of 95%. The implications of this research extend to the development of nanomaterial-based platforms for cellular identification, holding promise for potential applications in real time in-vivo cell differentiation monitoring.This study underlines the pivotal role of nanotubes in delineating the diverse micro-environments of distinct macrophage phenotypes for clinical research. It emphasizes the potential of short DNA sequences and machine learning in characterizing and classifying cell phenotypes, offering valuable insights into the intersection of nanotechnology and biomedical research.This innovative approach holds great promise in advancing our understanding of dynamic cellular processes, disease states, disease progression, and response to stimuli in-vivo. The platform’s sensitivity to minute changes in the Near Infrared spectrum positions it as a valuable tool for researchers and clinicians. It facilitates the real time monitoring of cellular behavior within living systems, offering insights that extend to both fundamental research and clinical applications. The implications of this research pave the way for future developments in nanotechnology and biomedicine, bridging the gap between spectral analysis and cellular dynamics for enhanced diagnostic and therapeutic interventions. Figure 1

DNAzyme and controllable cholesterol stacking DNA machine integrates dual-target recognition CTCs enable homogeneous liquid biopsy of breast cancer

Although circulating tumor cells (CTCs) have demonstrated considerable importance in liquid biopsy, their detection is limited by low concentrations and complex sample components. Herein, we developed a homogeneous, simple, and high-sensitivity strategy targeting breast cancer cells. This method was based on a non-immunological stepwise centrifugation preprocessing approach to isolate CTCs from whole blood. Precise quantification is achieved through the specific binding of aptamers to the overexpressed mucin 1 (MUC1) and human epidermal growth factor receptor 2 (HER2) proteins of breast cancer cells. Subsequently, DNAzyme cleavage and parallel catalytic hairpin assembly (CHA) reactions on the cholesterol-stacking DNA machine were initiated, which opened the hairpin structures T-Hg2+-T and C–Ag+-C, enabling multiple amplifications. This leads to the fluorescence signal reduction from Hg2+-specific carbon dots (CDs) and CdTe quantum dots (QDs) by released ions. This strategy demonstrated a detection performance with a limit of detection (LOD) of 3 cells/mL and a linear range of 5–100 cells/mL. 42 clinical samples have been validated, confirming their consistency with clinical imaging, pathology findings and the folate receptor (FR)-PCR kit results, exhibiting desirable specificity of 100% and sensitivity of 80.6%. These results highlight the promising applicability of our method for diagnosing and monitoring breast cancer.

Multispectral 3D DNA Machine Combined with Multimodal Machine Learning for Noninvasive Precise Diagnosis of Bladder Cancer.

Extracellular vesicle (EV) molecular phenotyping offers enormous opportunities for cancer diagnostics. However, the majority of the associated studies adopted biomarker-based unimodal analysis to achieve cancer diagnosis, which has high false positives and low precision. Herein, we report a multimodal platform for the high-precision diagnosis of bladder cancer (BCa) through a multispectral 3D DNA machine in combination with a multimodal machine learning (ML) algorithm. The DNA machine was constructed using magnetic microparticles (MNPs) functionalized with aptamers that specifically identify the target of interest, i.e., five protein markers on bladder-cancer-derived urinary EVs (uEVs). The aptamers were hybridized with DNA-stabilized silver nanoclusters (DNA/AgNCs) and a G-quadruplex/hemin complex to form a sensing module. Such a DNA machine ensured multispectral detection of protein markers by fluorescence (FL), inductively coupled plasma mass spectrometry (ICP-MS), and UV-vis absorption (Abs). The obtained data sets then underwent uni- or multimodal ML for BCa diagnosis to compare the analytical performance. In this study, urine samples were obtained from our prospective cohort (n = 45). Our analytical results showed that the 3D DNA machine provided a detection limit of 9.2 × 103 particles mL-1 with a linear range of 4 × 104 to 5 × 107 particles mL-1 for uEVs. Moreover, the multimodal data fusion model exhibited an accuracy of 95.0%, a precision of 93.1%, and a recall rate of 93.2% on average, while those of the three types of unimodal models were no more than 91%. The elevated diagnosis precision by using the present fusion platform offers a perspective approach to diminishing the rate of misdiagnosis and overtreatment of BCa.

Plant Synthetic Promoters

This article examines the structure and functions of the plant synthetic promoters frequently used to precisely regulate complex regulatory routes. It details the composition of native promoters and their interacting proteins to provide a better understanding of the tasks associated with synthetic promoter development. The production of synthetic promoters is performed by relatively small libraries produced generally by basic molecular or genetic engineering methods such as cis-element shuffling or domain swapping. The article also describes the preparation of large-scale libraries supported by synthetic DNA fragments, directed evolution, and machine or deep-learning methodologies. The broader application of novel, synthetic promoters reduces the prevalence of homology-based gene silencing or improves the stability of transgenes. A particularly interesting group of synthetic promoters are bidirectional forms, which can enable the expression of up to eight genes by one regulatory element. The introduction and controlled expression of several genes after one transgenic event strongly decreases the frequency of such problems as complex segregation patterns and the random integration of multiple transgenes. These complications are commonly observed during the transgenic crop development enabled by traditional, multistep transformation using genetic constructs containing a single gene. As previously tested DNA promoter fragments demonstrate low complexity and homology, their abundance can be increased by using orthogonal expression systems composed of synthetic promoters and trans-factors that do not occur in nature or arise from different species. Their structure, functions, and applications are rendered in the article. Among them are presented orthogonal systems based on transcription activator-like effectors (dTALEs), synthetic dTALE activated promoters (STAPs) and dCas9-dependent artificial trans-factors (ATFs). Synthetic plant promoters are valuable tools for providing precise spatiotemporal regulation and introducing logic gates into the complex genetic traits that are important for basic research studies and their application in crop plant development. Precisely regulated metabolic routes are less prone to undesirable feedback regulation and energy waste, thus improving the efficiency of transgenic crops.

Intelligent near-infrared light-activatable DNA machine with DNA wire nano-scaffold-integrated fast domino-like driving amplification for high-performance imaging in live biological samples

While there is significant potential for DNA machine-built enzyme-free fluorescence biosensors in the imaging analysis of live biological samples, they persist certain shortcomings. These encompass a deficiency of signal enrichment within a singular interface, uncontrolled premature activation during bio-delivery, and a slow reaction rate due to free nucleic acid collisions. In this contribution, we are committed to resolving the above challenges. Firstly, a single-interface-integrated domino-like driving amplification is constructed. In this conception, a specific target acts as the domino promotor (namely the energy source), initiating a cascading chain reaction that grafts onto a singular interface. Next, an 808 nm near-infrared (NIR) light-excited up-converting luminescence-induced light-activatable biosensing technique is introduced. By locking the target-specific identification segment with a photo-cleavage connector, the up-converted ultraviolet emission can activate target binding in a completely controlled manner. Moreover, a fast reaction rate is achieved by confining nucleic acid collisions within the surface of a DNA wire nano-scaffold, leading to a substantial enhancement in local contact concentration (30.8-fold increase, alongside a 15 times elevation in rate). When a non-coding microRNA (miRNA-221) is positioned as the model low-abundance target for proof-of-concept validation, our intelligent DNA machine demonstrates ultra-high sensitivity (with a limit of detection down to 62.65 fM) and good specificity for this hepatic malignant tumor-associated biomarker in solution detection. Going further, it is worth highlighting that the biosensing system can be employed to carry out high-performance imaging analysis in live bio-samples (ranging from the cellular level to the nude mouse body), thereby propelling the field of DNA machines in disease diagnosis.

Proximity-Guaranteed DNA Machine for Accurate Identification of Breast Cancer Extracellular Vesicles.

Breast cancer is one of the most diagnosed cancers worldwide. Precise diagnosis and subtyping have important significance for targeted therapy and prognosis prediction of breast cancer. Herein, we design a proximity-guaranteed DNA machine for accurate identification of breast cancer extracellular vesicles (EVs), which is beneficial to explore the subtype features of breast cancer. In our design, two proximity probes are located close on the same EV through specific recognition of coexisting surface biomarkers, thus being ligated with the help of click chemistry. Then, the ligated product initiates the operation of a DNA machine involving catalytic hairpin assembly and clusters of regularly interspaced short palindromic repeats (CRISPR)-Cas12a-mediated trans-cleavage, which finally generates a significant response that enables the identification of EVs expressing both biomarkers. Principle-of-proof studies are performed using EVs derived from the breast cancer cell line BT474 as the models, confirming the high sensitivity and specificity of the DNA machine. When further applied to clinical samples, the DNA machine is shown to be capable of not only distinguishing breast cancer patients with special subtypes but also realizing the tumor staging regarding the disease progression. Therefore, our work may provide new insights into the subtype-based diagnosis of breast cancer as well as identification of more potential therapeutic targets in the future.

Homogeneous electrochemical ratiometric biosensor for MircoRNA detection based on UiO-66-NH2 signal probe and waste-free entropy-driven DNA machine

The construction of efficient methods for highly sensitive and rapid detection of disease markers is essential for the early diagnosis of serious diseases. In this paper, taking advantage of the UiO-66-NH2 signal molecule in combination with a waste-free entropy-driven DNA machine, a novel homogeneous electrochemical ratiometric platform is developed to detect MircoRNA (miRNA). Metal-organic framework materials (UiO-66-NH2 MOF) and ferrocene were utilized as electrochemical signal tags and reference probes, respectively. The target-initiated waste-free three-dimensional (3D) entropy-driven DNA nanomachine is activated in the presence of miRNA, resulting in DNA-labeled-UiO-66-NH2 falling off from the electrode, leading to a decrease in the signal of UiO-66-NH2 at 0.83V. Our strategy can mitigate false positive responses induced by the DNA probes immobilized on electrodes in traditional distance-dependent signal adjustment ratiometric strategies. The proposed ratiometric platform demonstrates superior sensitivity (a detection limit of 9.8 fM), simplified operation, high selectivity, and high repeatability. The ratiometric biosensor is also applied to detect miRNA content in spiked serum samples.

Abstract A002: In-silico screening of race-specific endometrial cancer methylation markers using machine learning techniques

Abstract Targeted molecular therapy is a promising strategy for cancer treatment. Despite the benefits of these therapies, racial disparities in cancer therapy efficacy persist. To close this racial gap, there is a need to find race-specific biomarkers at the molecular level. Since abnormal DNA methylation has been linked with cancer and has a great potential to transform the diagnosis and treatment of cancer, the main objective of this study was to combine differential DNA methylation and machine learning techniques to identify race-specific methylation signature biomarkers in endometrial tumor samples from White and Black women. We performed genome wide Differentially Methylated CpG (DMCs) analysis in tumors from White patients (TWP) samples compared to tumors from Black patients (TBP) samples using Endometrial Carcinoma (EC) methylation and clinical data from The Cancer Genome Atlas (TCGA). We used supervised and unsupervised machine learning techniques to filter and select signature biomarkers. To evaluate the prognostic capacity of these genes, we performed univariate and multivariate survival analyses using Cox proportional hazards regression model from survival R package. By combining differential methylation CpGs and machine learning techniques, we reduced 704 differentially methylated CpGs to reliable race-specific epigenetic signature genes (ESGs) and Core- epigenetic signature genes (core-ESGs). An area under the curve (AUC) of 0.98 was achieved based on these signature genes. We further found that ESGs showed statistically significant overall survival differences between two racial groups. In addition, comparison of the mutational landscape showed differences in mutation frequencies in the ESGs between the two groups. By combining differential methylation analysis and machine learning techniques, we identified novel race-specific epigenetic signature genes in Black and White women with endometrial cancer. We further showed the potential of these gene in predicting survival differences, mutation, and transcriptomic differences in Black and White women. We propose that combined methylation and somatic mutation profiling of these novel race-specific signature genes can be used to develop potential therapeutic targets for diagnosis and treating endometrial cancer. Citation Format: Huma Asif, Grace Foley, Julie Kim. In-silico screening of race-specific endometrial cancer methylation markers using machine learning techniques [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A002.

Stimuli-responsive incremental DNA machine auto-catalyzed CRISPR-Cas12a feedback amplification permits ultrasensitive molecular diagnosis of esophageal cancer-related microRNA

Development of new diagnostic methods is essential for disease diagnosis and treatment. In this work, we present a stimuli-responsive incremental DNA machine auto-catalyzed CRISPR-Cas12a (SRI-DNA machine/CRISPR-Cas12a) feedback amplification for ultrasensitive molecular detection of miRNA-21, which is an important biomarker related closely to the initiation and development of cancers, such as esophageal cancer. Strategically, the powerful SRI-DNA machine and efficient trans-cleavage activity of the CRISPR-Cas12a system are ingeniously integrated via a rationally designed probe termed as stem-elongated functional hairpin probe (SEF-HP). The SRI-DNA machine begins with the target miRNA, the trigger of the reaction, binding complementarily to the SEF-HP, followed by autonomously performed mechanical strand replication, cleavage, and displacement circuit at multiple sites. This conversion process led to the amplified generation of numerous DNA activators that are complementary with CRISPR RNA (CrRNA). Once formed the DNA activator/CrRNA heteroduplex, the trans-cleavage activity of the CRISPR-Cas12a was activated to nonspecific cleavage of single-stranded areas of a reporter probe for fluorescence emission. Under optimal conditions, the target miRNA can be detected with a wide linear range and an excellent specificity. As a proof-of-concept, this SRI-DNA machine/CRISPR-Cas12a feedback amplification system is adaptable and scalable to higher-order artificial amplification circuits for biomarkers detection, highlighting its promising potential in early diagnosis and disease treatment.

A two-layer circuit cascade-based DNA machine for highly sensitive miRNA imaging in living cells.

Sensitive detection of microRNA (miRNA), one of the most promising biomarkers, plays crucial roles in cancer diagnosis. However, the low expression level of miRNA makes it extremely urgent to develop ultrasensitive and highly selective strategies for quantification of miRNA. Herein, a DNA machine is rationally constructed for amplified detection and imaging of low-abundance miRNA in living cells based on the toehold-mediated strand displacement reaction (TMSDR). The isothermal and enzyme-free DNA machine with low background leakage is fabricated by integrating two DNA circuits into a cascade system, in which the output of one circuit serves as the input of the other one. Once the DNA machine is transfected into breast cancer cells, the overexpressed miRNA-203 initiates the first-layer circuit through TMSDR, leading to the concentration variation of fuel strands, which further influences the assembly of hairpin DNA in the second-layer circuit and the occurrence of fluorescence resonance energy transfer (FRET) for fluorescence imaging. Benefiting from the cascade of the two-layer amplification reaction, the proposed DNA machine acquires a detection limit down to 4 fM for quantification of miR-203 and a 10 000-fold improvement in amplification efficiency over the single circuit. Therefore, the two-layer circuit cascade-based DNA machine provides an effective platform for amplified analysis of low-abundance miRNA with high sensitivity, which holds great promise in biomedical and clinical research.

Viral Genomic DNA Packaging Machinery.

Tailed double-stranded DNA bacteriophage employs a protein terminase motor to package their genome into a preformed protein shell-a system shared with eukaryotic dsDNA viruses such as herpesviruses. DNA packaging motor proteins represent excellent targets for antiviral therapy, with Letermovir, which binds Cytomegalovirus terminase, already licensed as an effective prophylaxis. In the realm of bacterial viruses, these DNA packaging motors comprise three protein constituents: the portal protein, small terminase and large terminase. The portal protein guards the passage of DNA into the preformed protein shell and acts as a protein interaction hub throughout viral assembly. Small terminase recognises the viral DNA and recruits large terminase, which in turn pumps DNA in an ATP-dependent manner. Large terminase also cleaves DNA at the termination of packaging. Multiple high-resolution structures of each component have been resolved for different phages, but it is only more recently that the field has moved towards cryo-EM reconstructions of protein complexes. In conjunction with highly informative single-particle studies of packaging kinetics, these structures have begun to inspire models for the packaging process and its place among other DNA machines.

Self-Assembled DNA Machine and Selective Complexation Recognition Enable Rapid Homogeneous Portable Quantification of Lung Cancer CTCs.

In this study, we systematically investigated the interactions between Cu2+ and various biomolecules, including double-stranded DNA, Y-shaped DNA nanospheres, the double strand of the hybridization chain reaction (HCR), the network structure of cross-linked HCR (cHCR), and small molecules (PPi and His), using Cu2+ as an illustrative example. Our research demonstrated that the coordination between Cu2+ and these biomolecules not only is suitable for modulating luminescent material signals through complexation reactions with Cu2+ but also enhances signal intensities in materials based on chemical reactions by increasing spatial site resistance and local concentration. Building upon these findings, we harnessed the potential for signal amplification in self-assembled DNA nanospheres and the selective complexation modulation of calcein in conjunction with the aptamer targeting mucin 1 as a recognition probe. We applied this approach to the analysis of circulating tumor cells, with the lung cancer cell line A549 serving as a representative model. Our assay, utilizing both a fluorometer and a handheld detector, achieved impressive detection limits of ag/ml and single-cell levels for mucin 1 and A549 cells, and this approach was successfully validated using 46 clinical samples, yielding 100% specificity and 86.5% sensitivity. Consequently, our strategy has paved the way for more portable and precise disease diagnosis.

Ratiometric electrochemical biosensor based on lateral movement of multi-pedal DNA tetrahedron machine on biomimetic interface

In this work, a lateral moving multi-pedal DNA tetrahedron machine (MTM) is designed and coupled with dual-signal output system to construct a biomimetic electrochemical ratiometric strategy for ultrasensitive target DNA analysis. The tetrahedral structure provided rigid support for the pedal, ensuring efficient replacement of the rail chain modified with ferrocene. By conjugating cholesterol molecules to one vertex of MTM, it is decorated on a lipid bilayer. This molecular architecture confers lateral movement of MTM on an electrode surface while prevents its detachment from the system. The methylene blue tagged hairpin probe provides constant power to support MTM swim on lipid bilayer. Compared with the conventional motion mode, the lateral moving mechanism has the fastest reaction rate and the highest signal-to-noise ratio. Additionally, the dual-signal reporting system further improves the accuracy of target detection on the basis of ensuring motion efficiency. The work improved movement efficiency and shortened time fragment. A linear relationship between the ratio value of two reporters and target DNA concentration was observed from 0.5 fM to 50 pM with a detection limit of 28 aM. The lateral motion mode of DNA machine coalescing with ratiometric system made this sensing platform ultrasensitive and accurate, which holds new avenue of early diagnosis.

A computational model for structural dynamics and reconfiguration of DNA assemblies

Recent advances in constructing a structured DNA assembly whose configuration can be dynamically changed in response to external stimuli have demanded the development of an efficient computational modeling approach to expedite its design process. Here, we present a computational framework capable of analyzing both equilibrium and non-equilibrium dynamics of structured DNA assemblies at the molecular level. The framework employs Langevin dynamics with structural and hydrodynamic finite element models that describe mechanical, electrostatic, base stacking, and hydrodynamic interactions. Equilibrium dynamic analysis for various problems confirms the solution accuracy at a near-atomic resolution, comparable to molecular dynamics simulations and experimental measurements. Furthermore, our model successfully simulates a long-time-scale close-to-open-to-close dynamic reconfiguration of the switch structure in response to changes in ion concentration. We expect that the proposed model will offer a versatile way of designing responsive and reconfigurable DNA machines.

Allosteric DNAzyme-based encoder for molecular information transfer

Dynamic DNA nanotechnology plays a significant role in nanomedicine and information science due to its high programmability based on Watson-Crick base pairing and nanoscale dimensions. Intelligent DNA machines and networks have been widely used in various fields, including molecular imaging, biosensors, drug delivery, information processing, and logic operations. Encoders serve as crucial components for information compilation and transfer, allowing the conversion of information from diverse application scenarios into a format recognized and applied by DNA circuits. However, there are only a few encoder designs with DNA outputs. Moreover, the molecular priority encoder is hardly designed. In this study, we introduce allosteric DNAzyme-based encoders for information transfer. The design of the allosteric domain and the recognition arm allows the input and output to be independent of each other and freely programmable. The pre-packaged mode design achieves uniformity of baseline dynamics and dynamics controllability. We also integrated non-nucleic acid molecules into the encoder through the aptamer design of the allosteric domain. Furthermore, we developed the 2n-n encoder and the Endo IV-assisted priority encoder inspired by immunoglobulin's molecular structure and effector patterns. To our knowledge, the proposed encoder is the first enzyme-free DNA encoder with DNA output, and the priority encoder is the first molecular priority encoder in the DNA reaction network. Our encoders avoid complex operations on a single molecule, and their simple structure facilitates their application in complex DNA circuits and biological scenarios.

Platinum-DNA Origami Hybrid Structures in Concentrated Hydrogen Peroxide.

The DNA origami technique allows fast and large-scale production of DNA nanostructures that stand out with an accurate addressability of their anchor points. This enables the precise organization of guest molecules on the surfaces and results in diverse functionalities. However, the compatibility of DNA origami structures with catalytically active matter, a promising pathway to realize autonomous DNA machines, has so far been tested only in the context of bio-enzymatic activity, but not in chemically harsh reaction conditions. The latter are often required for catalytic processes involving high-energy fuels. Here, we provide proof-of-concept data showing that DNA origami structures are stable in 5 % hydrogen peroxide solutions over the course of at least three days. We report a protocol to couple these to platinum nanoparticles and show catalytic activity of the hybrid structures. We suggest that the presented hybrid structures are suitable to realize catalytic nanomachines combined with precisely engineered DNA nanostructures.

“One-to-many” signal-output strategy-based CRISPR/Cas12a system for sensitive label-free fluorescence detection of HBV-DNA

Although CRISPR/Cas12a systems significantly enhance the analytical accuracy and flexibility of fluorescent biosensors, their sensitivity is limited by traditional “one-to-one” mediation types and ineffective signal-output turnover routes. Herein, we demonstrate a “one-to-many” signal-output strategy-based CRISPR/Cas12a systems resembling a “seaweed” to enhance the sensitivity. Based on dendrimer DNA from high-dimensional hybridization chain (HCR) of three hairpin-free DNA building blocks, the 3D magnetic DNA machine was created. The HBV-DNA initiates the rolling circle amplification (RCA) reaction and produces DNA nanowires to activate the CRISPR/Cas12a system. The trans-cleavage of the “seaweed root” by CRISPR/Cas12a system left dendrimer DNA in solution, thus, adding SYBR Green I (SG I) to the high-density DNA duplexes, achieving multiple-turnover label-free fluorescence signal output demonstrated and a low LOD (1.502 pM). However, in the absence of target, the blocked RCA failed to activate the CRISPR/Cas12a system, resulting in complete separation from substrate and negligible fluorescence signals. Moreover, the mandatory RCA-based pre-amplification of the DNA activator could efficiently trigger the multiple-turnover trans-cleavage activity of Cas12a. it can cleave one single-stranded linker of “seaweed-like” DNA machine, thereby releasing massive DNA duplex-enriched dendrimer DNA with a “one-to-many” signal-output turnover. By coupling the periodically extended Cas12a activator generated by RCA with hyperbranched DNA duplex by high-dimensional HCR, compact 3D extension structures were formed, achieving high-density fluorescence distribution in focal volume, avoiding signal dilution and ensuring high enhancement. Additionally, spiked recoveries in physiological media exceeded 95%, demonstrating the potential application of such platforms in clinical diagnosis.