Method and device for carrying out property analysis on nucleic acid nanostructure

Abstract

The invention relates to the technical field of biology, and discloses a method and device for carrying out property analysis on a nucleic acid nanostructure, and the method comprises the following steps: obtaining single molecule positioning imaging data of the nucleic acid nanostructure, and carrying out preprocessing to obtain space information and time information of the nucleic acid nanostructure; determining a profile curve of the nucleic acid nanostructure according to the spatial information, dividing the profile curve into a plurality of chain segments, calculating the length L of the chain segments through the spatial coordinates of the end points at the two ends of the chain segments, and calculating the angle correlation cos theta (L) through the unit vectors of the two end points with the distance of L; the length L of the chain segment and the average value lt of the angle correlation when the length of the chain segment is L are calculated; cos theta (L) gt; calculating the continuous length P of the nucleic acid nanostructure according to the relationship, and determining quantitative analysis on the structural rigidity; and determining quantitative analysis on the site accessibility, and performing correlation analysis on the structural rigidity and the site accessibility. The present invention provides an accurate quantitative assessment of structural rigidity and / or site accessibility of nucleic acid nanostructures.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and more specifically to a method and a device for analyzing properties of nucleic acid nanostructures. Background Art

[0002] Structural DNA nanotechnology is able to create complex, customized three-dimensional nanostructures with precise nucleotide resolution. This is achieved through bottom-up self-assembly of complementary sequences, ultimately facilitating the design of programmable molecular structures. The main goals of structural DNA nanotechnology include: (1) constructing highly ordered structures that self-assemble from single DNA motifs, including 1D, 2D, and ultimately 3D. (2) Using DNA nanostructures to assemble nanoscale elements into precise three-dimensional structures is of great significance to structural biology, nanomedicine, and single-molecule detection.

[0003] In the design of higher-order DNA structures, the most commonly used principle is the parallel arrangement of multiple double-stranded DNAs to produce multi-helix bundles. DNA nanobundles can be assembled from short oligonucleotides only or folded using long single-stranded scaffolds with the help of the DNA origami concept. DNA origami is a widely used technique for folding DNA chains into nanoscale structures. To achieve more complex structures, DNA chains can be arranged into large-periodic lattices with bundles. Honeycomb lattices based on six-helix bundles (6HBs) and tetragonal lattices based on four-helix bundles (4HBs) have been widely used. DNA nanobundles are fascinating materials for a variety of applications and can be used as connectors in single-molecule force spectroscopy, act as compressive load-bearing elements when fabricating nanoscale three-dimensional tensile structures, and act as connection templates for other nanomaterials at designated addressable sites through user-defined specific interactions. The field of structural design and fabrication of DNA nanotechnology requires DNA nanostructures with precise functions and mechanical properties. The successful realization of these structures largely relies on the folded conformation of addressable sites, which is crucial for connecting downstream host molecules and achieving the desired functions. However, it is worth noting that currently more than 10% of the addressable sites are defective, which has an adverse effect on the overall structural performance. Optimizing the best connectivity performance of the sites is essential to ensure the functionality and reliability of DNA nanostructures. In order to advance the fabrication of complex nanodevices, a comprehensive understanding of the mechanical properties and site accessibility behaviors of different individual DNA motifs in DNA nanostructures is necessary. Therefore, the relationship between the mechanical properties of DNA nanostructures and their binding site accessibility must be quantitatively elucidated to provide valuable guidance for the DNA nanofabrication process.

[0004] In the field of DNA nano research, quantification of the mechanical properties of DNA nanobundles is usually achieved through two main methods. The first method is to directly measure the structural rigidity of DNA nanobundles using magnetic tweezers. However, this method has limitations such as low throughput and complex operation. The second method is to analyze images obtained by characterizing individual structures using gas phase AFM and TEM. The persistence length calculated using the worm-like chain model is then used as a measure of structural rigidity. This method has advantages such as high throughput and has been widely used to evaluate the structural rigidity of DNA nanobundles. The persistence length is a widely accepted physical parameter for characterizing the structural rigidity of polymers.

[0005] There are two main methods for evaluating the accessibility of DNA nanobeam sites, which provide important data support at different levels. The first method is to measure the apparent hybridization rate by quantifying the overall fluorescence change of molecules in solution. This method uses the change in fluorescence signal generated when fluorescently labeled imaging probes bind to target molecules to evaluate the accessibility of molecules. The advantage of overall fluorescence measurement technology is that it is simple and fast to operate. However, this method may not provide detailed information at the level of individual molecules because it reflects the average situation of the entire sample. The second method is to use single-molecule technology, such as DNA-PAINT, to quantify the accessibility of individual functional single chains at molecular resolution. DNA-PAINT technology can observe the binding and dissociation process of individual molecules under a microscope by using specific imaging probes and fluorescent labels. The advantage of this method is its high resolution and single-molecule level accuracy, which can reveal the dynamic behavior and interaction of molecules at the microscopic level. However, single-molecule technology usually requires complex experimental setup and data analysis.

[0006] DNA nanoscale topography point accumulation (PAINT) super-resolution microscopy is an effective tool for characterizing DNA nanomaterials. It can achieve ultra-high spatial resolution (sub-5 nm) and quantitatively evaluate the site accessibility of addressable sites within DNA nanostructures. In this technology, the blinking required for stochastic super-resolution imaging is achieved by transiently binding short dye-labeled oligonucleotides (imaging strands) to their complementary target addressing sites. In order to explore the relationship between the structural rigidity of DNA nanobeams and the accessibility of addressable sites, this application designs a DNA-PAINT visualization and analysis framework to simultaneously obtain geometric and accessibility information. This method can quantitatively evaluate the structural rigidity of a single DNA nanobeam, the site accessibility of each addressable site, and the hybridization dynamics in solution. Summary of the invention

[0007] The object of the present invention is to provide a method and device for analyzing the properties of nucleic acid nanostructures, providing an accurate quantitative assessment of the structural rigidity and / or site accessibility of nucleic acid nanostructures.

[0008] In one aspect, the present application discloses a method for analyzing properties of a nucleic acid nanostructure, comprising:

[0009] S1. The nucleic acid nanostructure includes a nucleic acid nanobundle or a plurality of nucleic acid nanobundles connected to each other, and single-molecule localization imaging data of the nucleic acid nanostructure is obtained by microscope, and the single-molecule localization imaging data is preprocessed to obtain data of the nucleic acid nanostructure;

[0010] S2. Obtaining spatial information of the nucleic acid nanostructure from the data of the nucleic acid nanostructure, wherein the spatial information includes spatial coordinates of a plurality of addressable sites;

[0011] S3. determining a contour curve of the nucleic acid nanostructure according to the spatial information, wherein the contour curve is divided into a plurality of segments, and calculating a segment length L by spatial coordinates of endpoints at both ends of the segment, and calculating an angle correlation cosθ(L) by unit vectors of two endpoints with a distance L on the contour curve;

[0012] S4. The average value of the segment length L and the angle correlation on the profile curve when the segment length is L<cosθ(L)> Calculate the persistence length P of the nucleic acid nanostructure when the segment length is L based on the relationship between the chain length and the molecular weight, and determine the quantitative analysis of the structural rigidity of the nucleic acid nanostructure according to the persistence length P;

[0013] The structural rigidity includes the ability of the nucleic acid nanostructure to resist deformation when subjected to external forces.

[0014] In a preferred example, step S1 further includes:

[0015] S1.1 Acquire point cloud data of fluorescent groups characterizing nucleic acid nanostructure samples by single-molecule localization microscopy;

[0016] S1.2 filtering out fluorescent sites of poor quality from the point cloud data, performing drift correction, and obtaining a super-resolution reconstructed image of the nucleic acid nanostructure;

[0017] S1.3 performs single particle identification, and obtains data of each nucleic acid nanostructure through clustering algorithm and / or manual identification, wherein the data includes spatial information and temporal information.

[0018] In a preferred example, step S3 further includes:

[0019] S3.1 obtain the spatial coordinates of N addressable sites on the nucleic acid nanostructure, and determine the contour curve of the nucleic acid nanostructure according to the spatial information;

[0020] S3.2 using an interpolation algorithm to increase the N addressable sites on the contour curve to M endpoints, forming the chain segment between every two endpoints, wherein M>N;

[0021] S3.3 The segment length L is calculated by the spatial coordinates of the endpoints at both ends of the segment, the unit vector is calculated by the spatial coordinates of each endpoint on the contour curve and the previous adjacent endpoint, and the angle correlation cosθ(L) is calculated by the inner product between the unit vectors of the two endpoints with a distance of L on the contour curve.

[0022] In a preferred example, step S4 further includes:

[0023] The average value of the segment length L and the angle correlation on the profile curve when the segment length is L<cosθ(L)> The relationships include the worm-chain model;

[0024] The formula of the worm chain model includes:<cosθ(L)> =e^(-L / (2P)),

[0025] The persistence length P of the nucleic acid nanostructure when the segment length is L is calculated according to the formula of the worm chain model, and the quantitative analysis of the structural rigidity of the nucleic acid nanostructure is determined according to the persistence length P.

[0026] In a preferred embodiment, it also includes:

[0027] The morphology of the nucleic acid nanobundle includes four-helix bundle, six-helix bundle and eight-helix bundle. 4 to 16 addressable sites are distributed in the longitudinal direction of the nucleic acid nanobundle, and one or more single strands that can bind and dissociate with the imaging probe are distributed on each addressable site.

[0028] In a preferred embodiment, it also includes:

[0029] Sa. Quantitative analysis of structural rigidity using the method described above;

[0030] Sb. obtaining the data of the nucleic acid nanostructure by the method described in step S1, obtaining the time information of the nucleic acid nanostructure, and then determining the quantitative analysis of the site accessibility of the nucleic acid nanostructure;

[0031] Sc. performing a correlation analysis between the structural rigidity and the site accessibility;

[0032] The site accessibility includes the accessibility and operability of a specific sequence or domain on the nucleic acid nanostructure.

[0033] In a preferred embodiment, step Sa and step Sb are performed simultaneously on a molecular level based on the same single molecule localization imaging data without changing the natural state or environmental conditions of the nucleic acid nanostructure.

[0034] In a preferred embodiment, step Sb further comprises:

[0035] Sb.1 obtain the data of the nucleic acid nanostructure using the method described in step S1, and then obtain the time information of the nucleic acid nanostructure;

[0036] Sb.2 counting the number of fluorescent sites at each addressable site within the time information of the nucleic acid nanostructure to calculate the localization frequency, counting the average dark time of each addressable site according to the binding and dissociation kinetics, and determining the quantitative analysis of the site accessibility of the nucleic acid nanostructure according to the localization frequency or the average dark time;

[0037] Wherein, the positioning frequency includes the number of times the single-stranded and imaging probes at the addressable sites bind and dissociate per unit time; the binding and dissociation kinetics includes the analysis of the bright time and dark time in the photodynamic fingerprint of the addressable sites.

[0038] In a preferred embodiment, step Sc further comprises:

[0039] Sc.1 The first quantitative analysis of the structural rigidity of multiple nucleic acid nanostructures with different degrees of structural rigidity but the same initial morphology was performed within the same time period;

[0040] Sc.2 performing a second quantitative analysis of the site accessibility of the nucleic acid nanostructure within the same period of time;

[0041] Sc.3 determining the correlation between the structural rigidity and site accessibility of the plurality of nucleic acid nanostructures through the first quantitative analysis and the second quantitative analysis.

[0042] In a preferred embodiment, step Sc further comprises:

[0043] Sc.1 In the same time, the persistence length P of three nucleic acid nanobundles with different structural rigidity but the same initial morphology is calculated;

[0044] Sc.2: within the same time, counting the positioning frequency of the addressable sites on the nucleic acid nanobeam, and counting the average dark time at four positions of the addressable sites;

[0045] Sc.3 draw a box plot or perform a t-test on the average dark time at the four positions of the addressable sites of the three nucleic acid nanobeams to obtain position dependence, calculate the Poisson correlation coefficient between the persistence length P of the three nucleic acid nanobeams and the positioning frequency, and determine the correlation between the structural rigidity and the site accessibility based on the position dependence and / or the Poisson correlation coefficient.

[0046] In another aspect, the present application also provides a device for applying the method as described above, comprising a single molecule localization module, a quantitative evaluation module and a data analysis module;

[0047] The single-molecule localization module is used to obtain single-molecule localization imaging data of nucleic acid nanostructures through a microscope, and perform preprocessing to obtain spatial information and temporal information;

[0048] The quantitative evaluation module is used to quantitatively evaluate the structural rigidity according to the spatial information or to quantitatively evaluate the site accessibility according to the temporal information;

[0049] The data analysis module further analyzes the properties of the nucleic acid nanostructure or the relationship between different properties based on the quantitative evaluation data.

[0050] Compared with the prior art, the main differences and effects of the embodiments of the present invention are:

[0051] Ability to provide accurate numerical results to quantitatively evaluate the structural rigidity and site accessibility of nucleic acid nanostructures;

[0052] Furthermore, the measurement can be performed without changing the natural state or environmental conditions of the nucleic acid nanostructure, thereby ensuring the reliability and accuracy of the evaluation results and avoiding errors that may be introduced due to sample processing or environmental changes;

[0053] Furthermore, structural rigidity and site accessibility can be measured simultaneously during the same experimental process, effectively improving the efficiency of the experiment and reducing the required sample size.

[0054] Furthermore, it is of great significance for a deeper understanding of the applications of nucleic acid nanostructures in the fields of biosensing, drug delivery and nanoelectronics.

[0055] It should be understood that within the scope of the present invention, the above-mentioned technical features of the present invention and the technical features specifically described below (such as embodiments) can be combined with each other to form a new or preferred technical solution. Due to space limitations, they will not be described one by one here. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0057] Figure 1 It is a schematic diagram of the reconstruction process of a DNA-PAINT super-resolution image according to one embodiment of the present application.

[0058] Figure 2 It is a schematic diagram of calculating the persistence length in the quantitative evaluation of structural rigidity according to one embodiment of the present application.

[0059] Figure 3 It is a schematic diagram of the conformation of a six-helix bundle according to one embodiment of the present application.

[0060] Figure 4 It is a schematic diagram of the process of obtaining preliminary spatial information according to DNA-PAINT imaging in one embodiment of the present application.

[0061] Figure 5 It is a schematic flow diagram of the equilibrium contours of six-helix bundles with three degrees of structural rigidity according to one embodiment of the present application.

[0062] Figure 6 It is a schematic diagram of the calculation result of the persistence length in one embodiment of the present application.

[0063] Figure 7 1 is a schematic diagram of a processing flow for simultaneously and quantitatively evaluating the structural rigidity and site accessibility of a nucleic acid nanostructure according to one embodiment of the present application.

[0064] Figure 8 This is a schematic diagram of site accessibility assessment according to one embodiment of the present application.

[0065] Fig. 9 It is a schematic diagram of the spatial resolution of DNA-PAINT super-resolution image reconstruction according to one embodiment of the present application.

[0066] Fig.10 This is an accessibility analysis diagram based on positioning frequency in one embodiment of the present application.

[0067] Fig.11 It is a schematic diagram of site accessibility analysis based on binding and dissociation kinetics in one embodiment of the present application.

[0068] Fig.12 It is a schematic diagram of the position-dependent analysis of the six-helix bundle site accessibility according to one embodiment of the present application.

[0069] Fig.13 It is a schematic diagram of Poisson correlation analysis according to one embodiment of the present application. DETAILED DESCRIPTION

[0070] In the following description, many technical details are provided to help readers better understand the present application. However, those skilled in the art can understand that the technical solution claimed in the present application can be implemented even without these technical details and based on the changes and modifications of the following embodiments.

[0071] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0072] The present application discloses a method for analyzing properties of nucleic acid nanostructures, comprising:

[0073] S1. The nucleic acid nanostructure includes a nucleic acid nanobundle or a plurality of nucleic acid nanobundles connected to each other, and single-molecule localization imaging data of the nucleic acid nanostructure is obtained by a microscope, and the single-molecule localization imaging data is preprocessed to obtain data of the nucleic acid nanostructure;

[0074] S2. Obtaining spatial information of the nucleic acid nanostructure from the data of the nucleic acid nanostructure, the spatial information including spatial coordinates of a plurality of addressable sites;

[0075] S3. determining a contour curve of the nucleic acid nanostructure according to the spatial information, wherein the contour curve is divided into a plurality of segments, and the segment length L is calculated by the spatial coordinates of the endpoints at both ends of the segment, and the angle correlation cosθ(L) is calculated by the unit vectors of the two endpoints with a distance L on the contour curve;

[0076] S4. The average value of the segment length L and the angle correlation on the profile curve when the segment length is L<cosθ(L)> The relationship between the chain length and the length of the nucleic acid nanostructure is calculated to obtain the persistence length P of the nucleic acid nanostructure when the chain length is L, and the quantitative analysis of the structural rigidity of the nucleic acid nanostructure is determined according to the persistence length P; wherein the structural rigidity includes the ability of the nucleic acid nanostructure to resist deformation when subjected to an external force. The properties in this application include structural rigidity and site accessibility. In this application, structural rigidity, rigidity and mechanical properties are the same concept.

[0077] In one embodiment, step S1 further includes:

[0078] S1.1 Acquire point cloud data of fluorescent groups characterizing nucleic acid nanostructure samples by single-molecule localization microscopy;

[0079] S1.2 Screen out poor quality fluorescent sites from the point cloud data, perform drift correction, and obtain a super-resolution reconstructed image of the nucleic acid nanostructure;

[0080] S1.3 performs single particle identification, and obtains data of each nucleic acid nanostructure through clustering algorithm and / or manual identification, the data including spatial information and temporal information.

[0081] Example 1: In one embodiment, the preprocessing and export of single-molecule localization data is as follows Figure 1 As shown. This step is performed in sequence: a) Super-resolution image reconstruction, single-molecule localization processing is performed on the image queue collected by the microscope, including two-dimensional Gaussian fitting to obtain the initial point cloud data. According to the characteristics of the positioned point spread function, fluorescent sites with poor quality are screened out, such as sites with insufficient brightness, sites where multiple fluorescent molecules are excited simultaneously, and so on. Then the drift correction of the point cloud data is performed, including minimum entropy drift and redundant cross-correlation, to obtain a super-resolution image of the reconstructed nucleic acid nanobeam; b) Single particle identification, the spatial and temporal information of each structure is obtained through the DBSCAN clustering algorithm, and subsequent single particle analysis is prepared; c) Image export and contour marking, after rendering the point cloud data, the contours of the nucleic acid nanobeams are manually marked to prepare for the quantitative analysis of rigidity; d) Photodynamic information export, the optical timing signal of each structure is saved to prepare for the quantitative analysis of site accessibility.

[0082] In one embodiment, step S3 further includes:

[0083] S3.1 obtain the spatial coordinates of N addressable sites on the nucleic acid nanostructure, and determine the contour curve of the nucleic acid nanostructure according to the spatial information;

[0084] S3.2 uses an interpolation algorithm to increase the N addressable sites on the contour curve to M endpoints, forming a chain segment between every two endpoints, where M>N;

[0085] S3.3 The segment length L is calculated by the spatial coordinates of the endpoints at both ends of the segment, the unit vector is calculated by the spatial coordinates of each endpoint and the previous adjacent endpoint on the contour curve, and the angle correlation cosθ(L) is calculated by the inner product between the unit vectors of the two endpoints with a distance of L on the contour curve.

[0086] In one embodiment, step S4 further includes:

[0087] Average value of the segment length L and the angle correlation on the profile curve when the segment length is L<cosθ(L)> The relationships include the worm-chain model;

[0088] The formula for the worm-like chain model includes:<cosθ(L)> =e^(-L / (2P)), the persistence length P of the nucleic acid nanostructure when the chain length is L is calculated according to the formula of the worm chain model, and the structural rigidity of the nucleic acid nanostructure is quantitatively analyzed based on the persistence length P.

[0089] Embodiment 2: In one embodiment, as Figure 2As shown, the calculation method of the rigid metric persistence length is to calculate the persistence length by extracting spatial information from the point cloud data, and the persistence length of each type of nucleic acid nanobundle is calculated by fitting the average value of the cosine-cosine correlation along the contour curve. Figure 2 The left side shows the principle, Figure 2 The right side shows the relationship between the contour curve and the parameters related to the persistence length. Here, a fragment length of 23bp is used to calculate the cosine vector, which exceeds the crossover spacing of 21bp. It is worth noting that larger fragments produce similar persistence lengths. The steps are performed in sequence:

[0090] a) Obtaining the spatial coordinates of the chains: Taking the two-dimensional spatial coordinates of three chains as an example (in nanometers), these spatial coordinates are shown in the following table:

[0091] Cline1={(0,0),(40,0),(79.47,-6.49),(117.37,-19.29),(152.68,-38.08),(190.58,-50.88),(230.05,-57.37),(270.05,-57.37)}

[0092] Cline2={(0,0),(40,0),(79.47,6.49),(119.47,6.49),(158.94,12.98),(198.94,12.98),(238.41,19.47),(278.41,19.47)}

[0093] Cline3={(0,0),(40,0),(79.47,-6.49),(119.47,-6.49),(158.94,0),(198.94,0),(238.41,6.49),(276.31,19.29)}

[0094] b) Perform data interpolation and smoothing: In order to obtain higher calculation accuracy, the interpolation algorithm is used in this application to interpolate the original 8 addressable sites of each chain into 35 endpoints. The result of interpolation is that each chain is divided into 34 segments at equal intervals. Assume that the arc length of the chain is s∈[0,1], and the coordinates of the 35 endpoints after interpolation are: C(s)={r i}_{i=1}^{35},r i =(x i ,y i );

[0095] The coordinates of these endpoints are denoted by r i =(x i ,y i), where i represents the serial number of the interpolation point. Interpolation makes the structure of the chain smoother and provides uniform discrete points for subsequent persistence length calculation.

[0096] c) Calculate the unit vector between adjacent endpoints: For each chain, the application first calculates the vector between adjacent endpoints. For the i-th endpoint and the i+1-th endpoint, the vector is: v i =r i+1 -r i =(x i+1 -x i ,y i+1 -y i ), for example, assuming the first endpoint is (40, 0), then the first vector is: v1 = (40, 0) - (0, 0) = (40, 0), then calculate the modulus of each vector, that is, the length of the vector: |v i |=√((x i+1 -x i ) 2 +(y i+1 -y i ) 2 ), for example, the modulus of the first vector is: |v1| = √((40) 2 +(0) 2 )=40, normalize each vector to get the unit vector: V i =v i / |v i | For example, the unit vector of the first vector is: V1 = (40, 0) / 40 = (1, 0). Repeat the above process for all adjacent endpoints to calculate the unit vectors between all adjacent endpoints of each chain.

[0097] d) Calculation of angle correlation: Calculate the angle correlation between segments, that is, the inner product between the unit vectors of k adjacent segments. For each unit vector V of two adjacent k segments i V i+k , its inner product is expressed as: <cosθ i >=V i ·V i+k =(x i+1 -x i )(x i+k+1 -x i+k )+(y i+1 -y i )(y i+k+1 -y i+k ) / |v i ||v i+k |

[0098] This formula is used to quantify the directional difference between two adjacent k segments, that is, the angular correlation between them. By calculating the angular correlation at multiple different intervals k, the application can obtain<cosθ(L)> , that is, the relationship between the angle correlation and the segment length L. Table 1 shows the calculation results.

[0099] Table 1. Example calculation results

[0100]

[0101]

[0102] e) Fitting the relationship between the angle correlation and the chain length to calculate the persistence length P: According to the worm-like chain model, the angle correlation between unit vectors and the length L of the chain between them is exponentially decayed:<cosθ(L)> =e^(-L / (2P)); where P is the persistence length and L is the segment length. In this example, the segment length L is the interval between adjacent endpoints. After interpolation, the length of each segment is approximately the distance between each two endpoints. Based on the calculated angle correlation data<cosθ(L)> , the persistence length P obtained by fitting in this application is equal to 150.38nm.

[0103] In one embodiment, it further includes:

[0104] The morphologies of nucleic acid nanobundles include four-helix bundles, six-helix bundles and eight-helix bundles. There are 4 to 16 addressable sites distributed in the longitudinal direction of the nucleic acid nanobundle, and each addressable site is distributed with one or more single strands that can bind and dissociate with the imaging probe.

[0105] In one embodiment, it also includes: the nucleic acid nanobundle includes a honeycomb lattice based on six-helix bundles (6HBs), 8 addressable sites are evenly distributed in the longitudinal direction of the nucleic acid nanobundle, and 4 single strands that can bind and dissociate with the imaging probe are distributed on each addressable site. In one embodiment, the nucleic acid nanostructure includes a DNA nanostructure, a nucleic acid origami structure, and a DNA origami structure. In one embodiment, the nucleic acid nanobundle includes a DNA nanobundle and a 6HB origami structure.

[0106] Example 3: In one example, it is shown how to use the spatial information of DNA-PAINT to perform quantitative calculations of the rigidity of a DNA nanobundle. In this application, a classic six-helix bundle design is selected, such as Figure 3As shown, they are arranged in a honeycomb lattice. Each addressable site actually includes 4 single strands, but because the distance between them is about 4.7nm, which is less than 5nm, they cannot be distinguished visually, so they are regarded as single strands on the same addressable site; the distance between each addressable site is 42.2nm, the diameter of the helical bundle is 7nm, and there are 11nt on each single strand; after positioning using DNA-PAINT, the experimental data is presented as a set of spatial coordinates, each coordinate corresponds to a single positioning signal detection, and finally forms a point cloud. The point cloud can be analyzed by rendering an image using these coordinates, using image-based analysis methods, or directly studying the point cloud itself.

[0107] like Figure 4 As shown in (a), during the DNA-PAINT process here, the transient and reversible binding interaction between the 10-nt Cy3B-modified imaging probe and the addressable site induces well-coordinated blinking events. Figure 4 (b) shows the morphological analysis of the six-helix bundle using DNA-PAINT data.

[0108] In the data processing stage, the DNA-PAINT raw data was preprocessed. This included generating super-resolution reconstruction images of individual DNA nanobeams, manually identifying and selecting the spatial positions of all addressable sites, and smoothing the spatial coordinates of all sites to obtain the contour curve of a single DNA nanobeam. The analysis in this application involves quantitative measurements derived from the spatial information of 8 addressable sites in the DNA-PAINT image, where the determined length is equivalent to 70% of the true length. Figure 5 The super-resolution reconstruction images of three 6HB origami structures with different rigidity captured by DNA-PAINT technology in this application are shown. The 6HB origami structures with better rigidity have more blue curves. Subsequently, this application extracted the two-dimensional equilibrium contour lines of a single 6HB origami structure from these DNA-PAINT images. Figure 6 As shown, Figure 6 On the left is the schematic diagram, which calculates the persistence length based on the contour lines obtained from the DNA-PAINT image. Figure 6 On the right are box plots of the persistence lengths of the three DNA nanobundles, and the calculated raw data are shown in Table 2 to quantitatively evaluate the rigidity of the 6HB origami structure. The quantitative calculation results are consistent with the distribution of the alignment profiles of the representative monomers.

[0109] Table 2. Raw data of persistence lengths of three rigid nucleic acid nanostructures, unit: nanometers

[0110]

[0111]

[0112] In one embodiment, Figure 7 As shown, it also includes:

[0113] Sa. Quantitative analysis of structural rigidity using the method described above;

[0114] Sb. obtaining the data of the nucleic acid nanostructure by the method as in step S1, obtaining the time information of the nucleic acid nanostructure, and then determining the quantitative analysis of the site accessibility of the nucleic acid nanostructure;

[0115] Sc. Conducting a correlation analysis between structural rigidity and site accessibility; wherein site accessibility includes the accessibility and operability of specific sequences or domains on nucleic acid nanostructures.

[0116] In one embodiment, step Sa and step Sb are performed simultaneously on a molecular level for quantitative analysis based on the same single molecule localization imaging data without changing the natural state or environmental conditions of the nucleic acid nanostructure.

[0117] Because the measurements can be performed without changing the natural state or environmental conditions of the nucleic acid nanostructure, the reliability and accuracy of the evaluation results are guaranteed, and errors that may be introduced due to sample processing or environmental changes are avoided; because the quantitative analysis of rigidity and site accessibility in this application are based on DNA-PAINT technology, they can be performed simultaneously, thereby improving experimental efficiency.

[0118] In one embodiment, step Sb further includes:

[0119] Sb.1 obtain the data of the nucleic acid nanostructure using the method in step S1, and then obtain the time information of the nucleic acid nanostructure;

[0120] Sb.2 counting the number of fluorescent sites at each addressable site within the time information of the nucleic acid nanostructure to calculate the localization frequency, counting the average dark time of each addressable site based on the binding and dissociation kinetics, and determining the quantitative analysis of site accessibility of the nucleic acid nanostructure based on the localization frequency or the average dark time;

[0121] The localization frequency includes the number of times the single-stranded and imaging probes at the addressable sites bind and dissociate per unit time; the binding and dissociation kinetics includes the analysis of the bright time and dark time in the photodynamic fingerprint of the addressable sites.

[0122] Example 4: In one embodiment, in order to quantitatively evaluate the site accessibility of addressable sites, DNA-PAINT data acquisition was performed in this application while maintaining consistent experimental conditions for unbiased comparison. Time information was extracted from the DNA-PAINT results after data preprocessing. This application uses positioning frequency as a measure of site accessibility, and dark time is also used as a quantitative standard for site accessibility in high-order analysis. During the imaging process, the fluorescently labeled free imaging probe will randomly bind and dissociate on the docking chain at the addressable site. High site accessibility indicates that the imaging probe has strong binding force and weak dissociation force after hybridization with the docking chain. Figure 7 The hybridization frequency in represents the number of hybridizations within a specific time range, which is the same as the concept of localization frequency. Therefore, the number of fluorescent sites is positively correlated with the intensity of site accessibility, because both strong binding and weak separation will lead to an increase in the number of fluorescent sites. Figure 8 shown.

[0123] Example 5: In one example, it is shown how to use the temporal information of DNA-PAINT data to quantitatively calculate the site accessibility of nucleic acid nanobeams. Fig. 9 As shown, the cross-sectional histogram analysis of the DNA-PAINT super-resolution reconstruction image shows that the average distance between addressable sites is 41.3nm. This value is very close to the distance of the theoretical design, indicating that the origami design is precisely aligned with the experimental analysis. In addition, the positioning accuracy measured by the Gaussian fit of the reconstructed image is ~7.1nm, and the resolution achieved is about 16.7nm, which ensures the accuracy of the timing signal, that is, the fluorescent sites at the addressable sites can be accurately circled in this application.

[0124] This application is Fig.10 Data analysis of site accessibility based on mapping frequency is presented in . Fig.10 (a) shows that the site accessibility is positively correlated with the sampling speed during the imaging process. Comparing the time sampling differences of three different rigid six-helix bundles, the visualization results show that the difference is not obvious. All addressable sites of the six-helix bundle are clearly visible after about 500 seconds. Fig.10 (b) in FIG. 3 shows that by randomly sampling 300 six-helix bundles, the number of fluorescent sites at the addressable sites of each structure is counted in this application, and the structures with intact addressable sites are as high as 85%. Based on this, Fig.10 (c) in the figure shows the accessibility heat map of the addressable sites of the three six-helix bundles obtained in this application. Then, in this application, the location frequency of all addressable sites on the six-helix bundle is counted to analyze the difference in site accessibility of different degrees of rigidity. Fig.10(d) shows the histogram and Gaussian fitting results showing that the localization frequencies of three six-helix bundles with different rigidity are: De0 (733), Del1 (699) and Del3 (720). Within the same acquisition time, the number of fluorescent sites of the three is very similar. In addition, Fig.10 (e) in Figure 1 shows that another statistical method for localization frequency is to plot the number of fluorescent sites detected per frame over time. Here, in this application, it can be seen that the number of fluorescent sites for all six-helix bundles increases linearly over time and the growth rate is basically the same. This shows that the accessibility of sites with different rigidities is similar. Fig.11 The data analysis of site accessibility based on binding and dissociation kinetics is presented in the paper, and the light and dark time of the photodynamic fingerprints of these addressable sites are comprehensively analyzed. The kinetic analysis, histograms and Gaussian fitting results show that three six-helix bundles of different stiffness exhibit very similar binding kinetics.

[0125] In one embodiment, step Sc further comprises:

[0126] Sc.1 The first quantitative analysis of the structural rigidity of multiple nucleic acid nanostructures with different degrees of structural rigidity but the same initial morphology was performed within the same time period;

[0127] Sc.2 A second quantitative analysis of the site accessibility of the nucleic acid nanostructures is performed statistically at the same time;

[0128] Sc.3 Determine the correlation between the structural rigidity and site accessibility of various nucleic acid nanostructures through the first quantitative analysis and the second quantitative analysis.

[0129] In one embodiment, step Sc further comprises:

[0130] Sc.1 In the same time, the persistence length P of three nucleic acid nanobundles with different structural rigidity but the same initial morphology is calculated;

[0131] Sc.2: In the same time, the positioning frequency of the addressable sites on the nucleic acid nanobeam is counted, and the average dark time at the four positions of the addressable sites is counted;

[0132] Sc.3 Draw a box plot or perform a t-test on the average dark time at the four positions of the addressable sites of the three nucleic acid nanobeams to obtain position dependence, calculate the Poisson correlation coefficient between the persistence length P and the localization frequency of the three nucleic acid nanobeams, and determine the correlation between structural rigidity and site accessibility based on the position dependence and / or Poisson correlation coefficient.

[0133] Using six-helix bundles as a model system, this application experimentally demonstrates a remarkable finding that the structural rigidity of nucleic acid nanobundles does not affect site accessibility. This finding challenges previous assumptions, corrects technical biases, and provides valuable insights into the relationship between mechanical properties and functionality of nucleic acid nanostructures.

[0134] Example 6: In one example, this application will demonstrate how to use the obtained rigidity quantitative data and site accessibility quantitative data to perform a deeper correlation analysis.

[0135] First, if Fig.12 As shown, in this application, the accessibility of addressable sites at different spatial positions on six-helix bundles with different rigidity is analyzed for comparison, where the average dark time is used to quantitatively describe the accessibility. Fig.12 (a) shows that position p1 exhibits the greatest change in mean dark time across all three rigid variants, with a large number of outliers. This suggests that p1 may experience position-specific effects that affect accessibility, perhaps due to structural or environmental changes at this end of the six-helix bundle. Position p2 has a slight decrease in median dark time relative to p1, with reduced variance. The distribution remains similar across deletions, suggesting that position-dependent effects are minimal in this region. Position p3 maintains similar medians across deletions but exhibits fewer outliers compared to p1, suggesting that accessibility is more consistent at this position. Position p4 also exhibits a relatively stable distribution, with medians that are closely consistent across deletions and a consistent range of dark times. This suggests that p4 may be less sensitive to position effects, particularly in the context of the six-helix arrangement. Overall, the boxplots indicate potential position-dependent accessibility, especially for p1, which shows a wider range of dark times and more pronounced differences between deletion variants. Then, Fig.12 (b) in the figure shows the p-values ​​of the paired t-tests for the six-helix bundle variants (Del0, Del1, Del3) at four positions (P1-P4) also calculated in this application. For most positions (P1 to P4), the differences in the accessibility of the addressable sites between the six-helix bundle variants (Del0, Del1, Del3) are not statistically significant, as indicated by the higher p-values ​​in the comparison. The t-test shows that the average dark time changes observed between these deletion variants did not reach a significant level, indicating that the position-dependent accessibility may be relatively consistent between deletions, at least within the experimental conditions and statistical thresholds applied.

[0136] In addition, the Pearson correlation coefficient of each six-helix bundle was calculated in this application to quantitatively describe the correlation between rigidity and accessibility. Fig.13A series of scatter plots are presented to illustrate the relationship between the rigidity (persistence length) and site accessibility (localization frequency) of three six-helix bundle structures of different rigidity (Del0, Del1 and Del3). Each sub-graph is labeled accordingly. The specific analysis results are as follows:

[0137] For Del0, the data points are densely distributed near the lower range of persistence lengths, and are slightly more dispersed as the length increases. The calculated Pearson correlation coefficient is -0.0454, indicating that the negative correlation is negligible. The p-value is 0.4916, indicating that this correlation lacks statistical significance.

[0138] The Del1 plot exhibits a similar distribution pattern, with data points scattered over a range of persistence lengths. The correlation coefficient is 0.0295, indicating that there is little positive correlation. The accompanying p-value is 0.6208, confirming the lack of statistical significance.

[0139] In the Del3 plot, the data points maintained a comparable distribution with a correlation coefficient of -0.0058, further confirming the lack of correlation. The p-value was 0.9219, indicating no statistically significant relationship.

[0140] Each plot is represented by a red dashed line representing a linear fit, visually emphasizing the weak correlation observed. The overall analysis emphasizes that changes in persistence length do not significantly affect the number of fluorescent sites, highlighting the independence of site accessibility and rigidity in these six-helix bundle configurations.

[0141] The null hypothesis in the hypothesis test here is that there is no correlation between rigidity (persistence length) and site accessibility (localization frequency). A low p-value (≤0.05) indicates strong evidence against the null hypothesis, indicating that the observed data are unlikely to occur under the assumption that there is no correlation. Therefore, the correlation is considered statistically significant. A high p-value (>0.05) indicates weak evidence against the null hypothesis, indicating that the observed correlation could easily occur by chance. In this case, the correlation is not statistically significant. The three six-helix bundles with different rigidities all showed high p-values, indicating that any observed correlation between persistence length and localization frequency is likely due to random factors and that there is no significant relationship between the two variables. This strengthens the conclusion that the rigidity of the six-helix bundle does not affect site accessibility.

[0142] In another aspect, the present application also provides a device for applying the above method, comprising a single molecule localization module, a quantitative evaluation module and a data analysis module;

[0143] The single-molecule localization module is used to obtain single-molecule localization imaging data of nucleic acid nanostructures through a microscope and perform preprocessing to obtain spatial and temporal information;

[0144] The quantitative evaluation module is used to quantitatively evaluate the structural rigidity based on spatial information or to quantitatively evaluate the site accessibility based on temporal information;

[0145] The data analysis module further analyzes the properties of the nucleic acid nanostructure or the relationship between different properties based on the quantitatively evaluated data.

[0146] It should be noted that in the claims and description of this patent, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one" do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0147] All documents mentioned in the present invention are cited as references in this application, just as each document is cited as reference individually. In addition, it should be understood that after reading the above teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the claims attached to this application.

Claims

1. A method for analyzing properties of nucleic acid nanostructures, characterized in that: Comprising: S1. The nucleic acid nanostructure includes one nucleic acid nanobundle or multiple nucleic acid nanobundles with a connection relationship. Obtain the single-molecule localization imaging data of the nucleic acid nanostructure through a microscope, and preprocess the single-molecule localization imaging data to obtain the data of the nucleic acid nanostructure; S2. Obtain the spatial information of the nucleic acid nanostructure from the data of the nucleic acid nanostructure, and the spatial information includes the spatial coordinates of multiple addressable sites; S3. Determine the contour curve of the nucleic acid nanostructure according to the spatial information. The contour curve is divided into multiple segments. Calculate the segment length L through the spatial coordinates of the endpoints at both ends of the segment, and calculate the angular correlation cosθ(L) through the unit vectors of two endpoints with a distance of L on the contour curve; S4. Calculate the persistence length P of the nucleic acid nanostructure when the segment length is L through the relationship between the segment length L and the average value <cosθ(L)> of the angular correlation when the segment length on the contour curve is L, and determine the quantitative analysis of the structural rigidity of the nucleic acid nanostructure according to the persistence length P; Wherein, the structural rigidity includes the ability of the nucleic acid nanostructure to resist deformation when subjected to an external force.

2. The method according to claim 1, characterized in that Step S1 further includes: S1.1 Obtain the point cloud data of the fluorescent group characterizing the nucleic acid nanostructure sample through single-molecule localization microscopy; S1.2 Screen out the fluorescent sites with poor quality from the point cloud data, perform drift correction, and obtain the super-resolution reconstruction image of the nucleic acid nanostructure; S1.3 Perform single-particle recognition, and obtain the data of each nucleic acid nanostructure through a clustering algorithm and / or manual recognition. The data includes spatial information and time information.

3. The method according to claim 1, characterized in that: Step S3 further includes: S3.1 Obtain the spatial coordinates of N addressable sites on the nucleic acid nanostructure, and determine the contour curve of the nucleic acid nanostructure according to the spatial information; S3.2 Use an interpolation algorithm to increase the N addressable sites on the contour curve to M endpoints, and form the segment between every two endpoints, where M > N; S3.3 Calculate the segment length L through the spatial coordinates of the endpoints at both ends of the segment, calculate the unit vector through the spatial coordinates of each endpoint on the contour curve and the previous adjacent endpoint, and calculate the angular correlation cosθ(L) through the inner product between the unit vectors of two endpoints with a distance of L on the contour curve.

4. The method according to claim 1, characterized in that Step S4 further includes: The relationship between the segment length L and the average value <cosθ(L)> of the angular correlation when the segment length on the contour curve is L includes the worm-like chain model; The formula of the worm-like chain model includes: <cosθ(L)) = e^(-L / (2P)), Calculate the persistence length P of the nucleic acid nanostructure when the segment length is L according to the formula of the worm-like chain model, and determine the quantitative analysis of the structural rigidity of the nucleic acid nanostructure according to the persistence length P.

5. The method according to claim 1, characterized in that Also included: The morphology of the nucleic acid nanobundle includes four-helix bundle, six-helix bundle and eight-helix bundle. 4 to 16 addressable sites are distributed in the longitudinal direction of the nucleic acid nanobundle, and one or more single strands that can bind and dissociate with the imaging probe are distributed on each addressable site.

6. The method according to claim 1, characterized in that Also includes: Sa. Determine the quantitative analysis of the structural rigidity of the nucleic acid nanostructure using the method as claimed in claim 1; Sb. obtaining the data of the nucleic acid nanostructure by the method described in step S1, obtaining the time information of the nucleic acid nanostructure, and then determining the quantitative analysis of the site accessibility of the nucleic acid nanostructure; Sc. performing a correlation analysis between the structural rigidity and the site accessibility; The site accessibility includes the accessibility and operability of a specific sequence or domain on the nucleic acid nanostructure.

7. The method according to claim 6, characterized in that Step Sa and step Sb are to simultaneously perform quantitative analysis at the molecular level based on the same single-molecule localization imaging data without changing the natural state or environmental conditions of the nucleic acid nanostructure.

8. The method according to claim 5, characterized in that Step Sb also includes: Sb.1 obtain the data of the nucleic acid nanostructure using the method described in step S1, and then obtain the time information of the nucleic acid nanostructure; Sb.2 counting the number of fluorescent sites at each addressable site within the time information of the nucleic acid nanostructure to calculate the localization frequency, counting the average dark time of each addressable site according to the binding and dissociation kinetics, and determining the quantitative analysis of the site accessibility of the nucleic acid nanostructure according to the localization frequency or the average dark time; Wherein, the positioning frequency includes the number of times the single-stranded and imaging probes at the addressable sites bind and dissociate per unit time; the binding and dissociation kinetics includes the analysis of the bright time and dark time in the photodynamic fingerprint of the addressable sites.

9. The method according to claim 6, characterized in that Step Sc further comprises: Sc.1 The first quantitative analysis of the structural rigidity of multiple nucleic acid nanostructures with different degrees of structural rigidity but the same initial morphology was performed within the same time period; Sc.2 performing a second quantitative analysis of the site accessibility of the nucleic acid nanostructure within the same period of time; Sc.3 determining the correlation between the structural rigidity and site accessibility of the plurality of nucleic acid nanostructures through the first quantitative analysis and the second quantitative analysis.

10. A device for applying the method according to any one of claims 1 to 9, characterized in that: Includes single-molecule localization module, quantitative evaluation module and data analysis module; The single-molecule localization module is used to obtain single-molecule localization imaging data of nucleic acid nanostructures through a microscope, and perform preprocessing to obtain spatial information and temporal information; The quantitative evaluation module is used to quantitatively evaluate the structural rigidity according to the spatial information or to quantitatively evaluate the site accessibility according to the temporal information; The data analysis module further analyzes the properties of the nucleic acid nanostructure or the relationship between different properties based on the quantitative evaluation data.

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