A method and apparatus for performing property analysis of nucleic acid nanostructures

Abstract

The application relates to the technical field of biology, and discloses a method and device for analyzing the properties of a nucleic acid nanostructure, which comprises obtaining single-molecule positioning imaging data of the nucleic acid nanostructure, pre-processing the data to obtain spatial 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 both ends of the chain segments, calculating the angle correlation cos theta (L) through the unit vectors of the two end points with a distance of L, calculating the persistence length P of the nucleic acid nanostructure through the relationship between the chain segment length L and the average value <cos theta (L)> of the angle correlation when the chain segment length is L, determining quantitative analysis of structural rigidity, determining quantitative analysis of site accessibility, and performing correlation analysis of the structural rigidity and the site accessibility. The application provides accurate quantitative evaluation of the structural rigidity and / or site accessibility of the nucleic acid nanostructure.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biotechnology, more particularly to a method and device for analyzing the properties of nucleic acid nanostructures. BACKGROUND

[0002] Structural DNA nanotechnology enables the creation of complex custom three-dimensional nanostructures with precise nucleotide resolution. This is achieved through the complementary sequence self-assembly from bottom to top, ultimately contributing to the design of programmable molecular structures. The main goals of structural DNA nanotechnology include: (1) constructing highly ordered structures self-assembled from individual DNA motifs, including 1D, 2D, and ultimately 3D. (2) Assembling nanoscale elements into precise three-dimensional structures using DNA nanostructures is of great significance to structural biology, nanomedicine, and single-molecule detection.

[0003] In the design of high-order DNA structures, the most commonly used principle is the parallel arrangement of multiple double-stranded DNA, thereby generating multi-helix bundles. DNA nanobundles can be assembled from short oligonucleotides or folded with long single-stranded scaffolds with the aid of DNA origami concepts. DNA origami is a widely used technology for folding DNA strands into nanoscale structures. To achieve more complex structures, DNA strands can be arranged into large-period lattices with a bundle-like shape. Honeycomb lattices based on six-helix bundles (6HBs) and square lattices based on four-helix bundles (4HBs) have been widely used. DNA nanobundles are fascinating materials suitable for a variety of applications, which can be used as linkers in single-molecule force spectroscopy, act as compression-bearing elements when manufacturing nanoscale three-dimensional stretched structures, and act as connection templates for other nanomaterials at specified addressable sites through user-defined specific interactions. The field of structural design and manufacturing of DNA nanotechnology requires DNA nanostructures with precise functions and mechanical properties. The successful implementation of these structures largely depends on the folding conformation of addressable sites, which is crucial for connecting downstream guest molecules and achieving the desired functions. However, it is worth noting that more than 10% of the addressable sites are defective, which has a negative impact on the overall structural performance. Optimizing the optimal connection performance of the site is crucial to ensure the functionality and reliability of the DNA nanostructure. In order to advance the manufacturing of complex nanodevices, it is necessary to comprehensively understand the mechanical properties and site accessibility behavior of different individual DNA motifs in DNA nanostructures. Therefore, it is necessary to quantitatively elucidate the relationship between the mechanical properties of DNA nanostructures and their binding site accessibility, providing valuable guidance for the DNA nanomanufacturing process.

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

[0005] Two main methods are used to assess the site accessibility of DNA nanowires, providing 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 when fluorescently labeled imaging probes bind to target molecules to assess the accessibility of molecules. The advantage of overall fluorescence measurement technology is its simple and fast operation. However, this method may not provide detailed information at the single molecule level, as it reflects the average situation of the entire sample. The second method is to use single molecule techniques such as DNA-PAINT to quantify the accessibility of individual functional single strands at a 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 techniques usually require complex experimental setup and data analysis.

[0006] DNA nanoscale topography imaging point accumulation (PAINT, Point Accumulation for Imaging in Nanoscale Topography) super-resolution microscopy is an effective tool for characterizing DNA nanomaterials. It can achieve ultra-high spatial resolution (sub-5 nanometers) and quantitatively evaluate the site accessibility of addressable sites within DNA nanostructures. In this technology, the required blinking for random super-resolution imaging is achieved by transiently binding short dye-labeled oligonucleotides (imaging strands) to their complementary target addressable sites. To explore the relationship between the structural rigidity of DNA nanowires 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 individual DNA nanowires, the site accessibility of each addressable site, and the hybridization kinetics in solution. SUMMARY

[0007] The present application aims to provide a method and device for analyzing the properties of a nucleic acid nanostructure, and to provide accurate quantitative evaluation of the structural rigidity and / or site accessibility of a nucleic acid nanostructure.

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

[0009] S1. The nucleic acid nanostructure comprises a nucleic acid nanowire or a plurality of nucleic acid nanowires connected together, and single-molecule localization imaging data of the nucleic acid nanostructure is obtained by microscopy, and data of the nucleic acid nanostructure is obtained by preprocessing the single-molecule localization imaging data;

[0010] S2. Spatial information of the nucleic acid nanostructure is obtained from the data of the nucleic acid nanostructure, and the spatial information comprises spatial coordinates of a plurality of addressable sites;

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

[0012] S4. A persistence length P of the nucleic acid nanostructure when the chain segment length is L is calculated by a relationship between the chain segment length L and an average value <cosθ(L)> of the angle correlation when the chain segment length is L, and quantitative analysis of structural rigidity of the nucleic acid nanostructure is determined according to the persistence length P;

[0013] Wherein, the structural rigidity comprises the ability of the nucleic acid nanostructure to resist deformation when subjected to an external force.

[0014] In one preferred embodiment, step S1 further comprises:

[0015] S1.1 Point cloud data of fluorescent groups characterizing a nucleic acid nanostructure sample is obtained by single-molecule localization microscopy;

[0016] S1.2 Poor-quality fluorescent sites are screened out from the point cloud data, drift correction is performed, and a super-resolution reconstruction image of the nucleic acid nanostructure is obtained;

[0017] S1.3 Single-particle recognition is performed, and data of each nucleic acid nanostructure is obtained by a clustering algorithm and / or manual recognition, and the data comprises spatial information and temporal information.

[0018] In one preferred embodiment, step S3 further comprises:

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

[0020] S3.2 increasing N addressable sites on the contour curve to M end points using an interpolation algorithm, forming a chain segment between each two end points, wherein M>N;

[0021] S3.3 calculating a chain segment length L through spatial coordinates of end points at both ends of the chain segment, calculating a unit vector through spatial coordinates of each end point and the previous adjacent end point on the contour curve, and calculating an angle correlation cosθ(L) through inner product between unit vectors of two end points on the contour curve with a distance of L.

[0022] In a preferred embodiment, step S4 further comprises:

[0023] A relationship between chain segment length L and an average value of angle correlation <cosθ(L)> when the chain segment length is L on the contour curve comprises a worm-like chain model;

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

[0025] Calculating a persistence length P of the nucleic acid nanostructure when the chain segment length is L according to the formula of the worm-like chain model, and determining a quantitative analysis of structural rigidity on the nucleic acid nanostructure according to the persistence length P.

[0026] In a preferred embodiment, further comprising:

[0027] The morphology of the nucleic acid nanobeam comprises a four-helix bundle, a six-helix bundle and an eight-helix bundle, and 4-16 addressable sites are distributed in the longitudinal direction of the nucleic acid nanobeam, and one or more single strands capable of binding and dissociating with an imaging probe are distributed on each addressable site.

[0028] In a preferred embodiment, further comprising:

[0029] Sa. a quantitative analysis of structural rigidity using the method as described above;

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

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

[0032] The site accessibility includes the accessibility and operability of specific sequences or domains on the nucleic acid nanostructure.

[0033] In a preferred embodiment, the step Sa and the step Sb are simultaneously quantitatively analyzed at a molecular level according to 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, the step Sb further comprises:

[0035] Sb.1 obtaining data of the nucleic acid nanostructure by the method as described in the step S1, and further obtaining 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 a localization frequency, counting an average dark time of each addressable site according to binding and dissociation kinetics, and determining a quantitative analysis of site accessibility of the nucleic acid nanostructure according to the localization frequency or the average dark time;

[0037] The localization frequency includes the number of binding and dissociation of single-stranded and imaging probes on the addressable site per unit time; and the binding and dissociation kinetics includes analysis of bright time and dark time in the photokinetic fingerprint of the addressable site.

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

[0039] Sc.1 statistically analyzing a first quantitative analysis of structural rigidity of a plurality of nucleic acid nanostructures with different structural rigidity but same initial morphology within the same time;

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

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

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

[0043] Sc.1 statistically analyzing a first quantitative analysis of structural rigidity of a plurality of nucleic acid nanostructures with different structural rigidity but same initial morphology within the same time;

[0044] Sc.2 statistically analyzing a second quantitative analysis of site accessibility of the nucleic acid nanostructure within the same time;

[0045] Sc.3 plots a box plot of the average dark time on four positions of addressable sites of three said nucleic acid nanowires or performs t-test to obtain position dependence, calculates the Poisson correlation coefficient of the persistence length P and the localization frequency of three said nucleic acid nanowires, and determines the correlation between the structural rigidity and the site accessibility according to 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 acquire single molecule localization imaging data of nucleic acid nanostructures by microscopy, and to obtain spatial information and temporal information by preprocessing;

[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 nanostructures or the relationship between different properties according to the quantitatively evaluated data.

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

[0051] Accurate numerical results can be provided, and the structural rigidity and site accessibility of nucleic acid nanostructures can be quantitatively evaluated;

[0052] Further, the measurement can be performed without changing the natural state or environmental conditions of the nucleic acid nanostructures, 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] Further, the structural rigidity and site accessibility can be measured simultaneously in the same experimental process, effectively improving the efficiency of the experiment and reducing the amount of samples required.

[0054] Further, it is of great significance for in-depth understanding of the application 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 application, each of the above technical features of the present application and each of the technical features specifically described below (such as the examples) can be combined with each other to form a new or preferred technical scheme. Due to the limited space, they will not be listed one by one here. BRIEF DESCRIPTION OF DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below.

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

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

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

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

[0061] Figure 5 is a schematic diagram of the process of drawing equilibrium profiles of six-helix bundles with three degrees of structural rigidity according to an embodiment of the present application.

[0062] Figure 6 is a schematic diagram of the calculation results of persistence length according to an embodiment of the present application.

[0063] Figure 7 is a schematic diagram of the process flow of simultaneously quantitatively evaluating the structural rigidity and site accessibility of nucleic acid nanostructures according to an embodiment of the present application.

[0064] Figure 8 is a schematic diagram of the evaluation of site accessibility according to an embodiment of the present application.

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

[0066] Figure 10 is a diagram of accessibility analysis based on localization frequency according to an embodiment of the present application.

[0067] Figure 11 is a schematic diagram of site accessibility analysis based on binding and dissociation kinetics according to an embodiment of the present application.

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

[0069] Figure 13 is a schematic diagram of Pearson correlation analysis according to an embodiment of the present application. DETAILED DESCRIPTION

[0070] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be appreciated that the present application can be practiced without the specific details and that numerous implementation variations, modifications, and adaptations are possible.

[0071] In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the drawings.

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

[0073] S1. The nucleic acid nanostructure comprises a nucleic acid nanobundle or multiple nucleic acid nanobundles connected together, single-molecule localization imaging data of the nucleic acid nanostructure is obtained by a microscope, and data of the nucleic acid nanostructure is obtained by preprocessing the single-molecule localization imaging data;

[0074] S2. Spatial information of the nucleic acid nanostructure is obtained from the data of the nucleic acid nanostructure, and the spatial information comprises spatial coordinates of multiple addressable sites;

[0075] S3. A profile curve of the nucleic acid nanostructure is determined according to the spatial information, the profile curve is divided into multiple chain segments, a chain segment length L is calculated by using spatial coordinates of end points at two ends of the chain segment, and an angle correlation cosθ(L) is calculated by using unit vectors of two end points with a distance of L on the profile curve;

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

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

[0078] S1.1. Point cloud data of fluorescent groups characterizing the nucleic acid nanostructure sample is obtained by single-molecule localization microscopy technology;

[0079] S1.2. Poor-quality fluorescent sites are screened out from the point cloud data, drift correction is performed, and a super-resolution reconstruction image of the nucleic acid nanostructure is obtained;

[0080] S1.3. Single-particle recognition is performed, data of each nucleic acid nanostructure is obtained by a clustering algorithm and / or manual recognition, and the data comprises spatial information and time 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 simultaneously excited, and so on. Then, 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 nanobundle; b) single particle identification, the spatial and temporal information of each structure is obtained through the DBSCAN clustering algorithm to prepare for subsequent single particle analysis; c) image export and contour line marking, after rendering the point cloud data, the contour lines of the nucleic acid nanobundle 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 obtains the spatial coordinates of N addressable sites on the nucleic acid nanostructure, and determines a contour curve of the nucleic acid nanostructure based on 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 each 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 angular correlation cosθ(L) is calculated by the inner product between the unit vectors of the two endpoints with a distance 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 wormwood chain model. The structural rigidity of the nucleic acid nanostructure is quantitatively analyzed based on the persistence length P.

[0089] Example 2: In one embodiment, Figure 2As shown, the calculation method of the rigidity metric Persistence Length is to calculate the persistence length from the spatial information extracted from the point cloud data, by fitting the average value of the cosine-cosine correlation along the contour curve, to calculate the persistence length of each type of nucleic acid nanobeam. 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, the cosine vector is calculated using a fragment length of 23 bp, which is longer than the 21 bp cross-distance. It is worth noting that larger fragments produce similar persistence lengths. This step is performed in turn:

[0090] a) Obtain the spatial coordinates of the chain: Take the two-dimensional spatial coordinates of the three chains as an example (in nanometers), which 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) 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 to divide each chain into 34 equal segments. Let the arc length of the chain be s ∈ [0, 1], and the coordinates of the 35 interpolated endpoints be: C(s) = {r i}_{i=1}^{35}, r i = (x i , y i );

[0095] The coordinates of these endpoints are represented as r i = (x i , y i), where i denotes 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) Calculation of unit vectors between adjacent endpoints: For each chain, the vector between adjacent endpoints is first calculated in this application. For the ith endpoint and the i+1th endpoint, its 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), the first vector is: v1 = (40, 0) - (0, 0) = (40, 0), then, the length of each vector, i.e. the length of the vector, is calculated: |v i | = √((x i+1 - x i ) 2 +(y i+1 - y i ) 2 ), for example, the length 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 vector between all adjacent endpoints of each chain.

[0097] d) Calculation of angle correlation: Calculate the angle correlation between the chain segments, i.e. the inner product between the unit vectors of two adjacent k segments. For each two adjacent k segment unit vectors V i V i+k , the inner product is represented 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] The formula is used to quantify the difference in orientation between two adjacent k-segments, i.e. the angular correlation between them. By calculating the angular correlation for a number of different intervals k, one can obtain in this application <cos0(L)>, the angular correlation as a function of the segment length L. Table 1 shows the results of the calculation.

[0099] Table 1. Example calculation results

[0100]

[0101]

[0102] e) Fitting the angular correlation to the length of the strand The persistence length P is calculated from the angular correlation between unit vectors and the segment length L between them according to the worm-like chain model: <cos0(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 approximated as the distance between each two endpoints. From the calculated angular correlation data <cos0(L)>, the persistence length P is fitted to be equal to 150.38 nm in this application.

[0103] In one embodiment, further comprising:

[0104] The nucleic acid nanobeam has a morphology including a four-helix bundle, a six-helix bundle, and an eight-helix bundle, and has 4-16 addressable sites distributed in the longitudinal direction of the nucleic acid nanobeam, and each addressable site has one or more single strands that can bind and dissociate with an imaging probe.

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

[0106] Example 3: In one embodiment, it is shown how to use the spatial information of DNA-PAINT to quantitatively calculate the rigidity of DNA nanobeam. In this application, a classic six-helix bundle design is selected, as shown in Figure 3As shown, they are arranged in a honeycomb lattice. Each addressable site actually consists of four single strands, but because the distance between them is approximately 4.7 nm, less than 5 nm, they are visually indistinguishable and are therefore considered single strands at the same addressable site. The distance between each addressable site is 42.2 nm, the diameter of the helical bundle is 7 nm, and each single strand has 11 nt. After positioning using DNA-PAINT, the experimental data is represented as a set of spatial coordinates, each corresponding to a single localization signal detection, ultimately forming a point cloud. This point cloud can be analyzed by rendering an image using these coordinates, applying 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] During the data processing phase, the DNA-PAINT raw data underwent preprocessing. This involved generating super-resolution reconstructions of individual DNA nanobundles, manually identifying and selecting the spatial locations of all addressable sites, and smoothing the spatial coordinates of all sites to obtain the profile of the individual DNA nanobundles. The analysis presented in this application involved quantitative measurements derived from the spatial information of eight addressable sites in the DNA-PAINT images, with the determined lengths corresponding 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 structure with better rigidity has more blue curves. Subsequently, this application extracted the two-dimensional equilibrium contour line of a single 6HB origami structure from these DNA-PAINT images. Figure 6 As shown, Figure 6 The left side is the schematic diagram, which shows the calculation of the persistence length based on the contour line obtained from the DNA-PAINT image. Figure 6 The right side shows a box plot of the persistence lengths of the three DNA nanobundles, and the raw data calculated to quantitatively assess the rigidity of the 6HB origami structure are shown in Table 2. 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, as shown in Figure 7 Further comprising:

[0113] Sa. performing quantitative analysis of structural rigidity using the method as described above;

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

[0115] Sc. performing correlation analysis of structural rigidity and site accessibility; wherein the site accessibility includes the contactability and operability of specific sequences or domains on the nucleic acid nanostructure.

[0116] In one embodiment, the steps Sa and Sb are quantitative analysis at the molecular level simultaneously 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 measurement 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 ensured, 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 the present application are both based on DNA-PAINT technology, they can be performed simultaneously, thus improving experimental efficiency.

[0118] In one embodiment, the step Sb further comprises:

[0119] Sb.1 obtaining data of the nucleic acid nanostructure using the method in step S1, and obtaining 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, statistically analyzing the average dark time of each addressable site according to the binding and dissociation kinetics, and determining the quantitative analysis of site accessibility of the nucleic acid nanostructure according to the localization frequency or the average dark time;

[0121] wherein the localization frequency includes the number of binding and dissociation of single-stranded and imaging probes on the addressable site per unit time; and the binding and dissociation kinetics includes analysis of bright time and dark time in the photodynamic fingerprint of the addressable site.

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

[0123] Example 5: In one embodiment, it is shown how to use the temporal information of DNA-PAINT data to quantitatively calculate the site accessibility of nucleic acid nanobeam. As shown in (a), the cross-sectional histogram analysis of the DNA-PAINT super-resolution reconstructed image shows that the average distance between addressable sites is 41.3 nm. This value is very close to the theoretically designed distance, indicating that the origami design is accurately aligned with experimental analysis. In addition, the localization precision measured by Gaussian fitting of the reconstructed image is ~ 7.1 nm, so the resolution achieved is about 16.7 nm, which guarantees the accuracy of the timing signal, i.e., the fluorescent sites at the addressable sites can be accurately circled in this application. Figure 9

[0124] This application demonstrates the data analysis of site accessibility based on localization frequency in (b). Figure 10 (a) in (b) shows that site accessibility is positively correlated with the sampling speed during the imaging process, and the difference in time sampling of three different rigid six-helix bundles is compared, and the visualization result shows that the difference is not obvious. All addressable sites of the six-helix bundle are clearly visible after about 500 seconds. Figure 10 (b) in (b) shows that by randomly sampling 300 six-helix bundles, this application counts the number of fluorescent sites at the addressable sites of each structure, and the structures that preserve the complete addressable sites are as high as 85%. Based on this, Figure 10 (c) in (c) shows that this application obtains the accessibility heat map of the addressable sites of the three six-helix bundles. Then, by counting the localization frequency of all addressable sites on the six-helix bundle, this application analyzes the difference in site accessibility of different degrees of rigidity. Figure 10 Figure 10 ​​​(d) in FIG. 6 shows the histogram and Gaussian fitting results of the localization frequency of the six-helix bundle with three different rigidities: De0(733), Del1(699), and Del3(720). The number of fluorescent spots of the three is very similar in the same acquisition time. In addition, Figure 10 (e) in FIG. 6 shows another statistical method of the localization frequency is to plot the number of fluorescent spots detected per frame as a function of time. Here, it can be seen in this application that the number of fluorescent spots of all six-helix bundles increases linearly with time and the growth rate is basically consistent. This shows that the site accessibility of different rigidities is similar. The data analysis of site accessibility based on binding dissociation kinetics is shown in Figure 11 (e) in FIG. 6 shows another statistical method of the localization frequency is to plot the number of fluorescent spots detected per frame as a function of time. Here, it can be seen in this application that the number of fluorescent spots of all six-helix bundles increases linearly with time and the growth rate is basically consistent. This shows that the site accessibility of different rigidities is similar. The data analysis of site accessibility based on binding dissociation kinetics is shown in

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

[0126] Sc.1 statistically analyzing the first quantitative analysis of the structural rigidity of a plurality of nucleic acid nanostructures with different structural rigidity degrees but the same initial morphology in the same time;

[0127] Sc.2 statistically analyzing the second quantitative analysis of the site accessibility of the nucleic acid nanostructure in the same time;

[0128] Sc.3 determining the correlation between the structural rigidity and the site accessibility of the plurality of nucleic acid nanostructures by the first quantitative analysis and the second quantitative analysis.

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

[0130] Sc.1 statistically analyzing the first quantitative analysis of the structural rigidity of a plurality of nucleic acid nanostructures with different structural rigidity degrees but the same initial morphology in the same time;

[0131] Sc.2 statistically analyzing the second quantitative analysis of the site accessibility of the nucleic acid nanostructure in the same time;

[0132] Sc.3 determining the correlation between the structural rigidity and the site accessibility of the plurality of nucleic acid nanostructures by the first quantitative analysis and the second quantitative analysis.

[0133] The present application, through the use of a six-helix bundle as a model system, has experimentally demonstrated a notable finding that the structural rigidity of a nucleic acid nanobundle 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 embodiment, the present application will demonstrate how to use the obtained quantitative data of rigidity and quantitative data of site accessibility for deeper correlation analysis.

[0135] First, as shown in Figure 12 , the present application analyzed the comparative analysis of the accessibility of addressable sites at different spatial positions on different rigid six-helix bundles, where the average dark time was used to quantitatively describe the accessibility. Figure 12 (a) of FIG. 6 shows that position p1 exhibits the largest change in average dark time across all three rigid variants, and there is a large number of outliers. This suggests that p1 can experience position-specific effects that affect accessibility, which can be due to structural or environmental changes at this end of the six-helix bundle. The median dark time for position p2 is slightly reduced relative to p1, with reduced variance. The distribution remains similar across deletions, indicating minimal position-dependent effects for this region. Position p3 maintains similar medians across deletions, but exhibits fewer outliers compared to p1, indicating more consistent accessibility at this position. Position p4 also exhibits a relatively stable distribution, with tight agreement in median values across deletions and consistent range of dark times. This suggests that p4 can be less sensitive to position effects, especially in the context of the six-helix arrangement. Overall, the box plots indicate potential position-dependent accessibility, especially for p1, which shows a wider range of dark times and more pronounced differences between deletion variants. Then, Figure 12 (b) of FIG. 6 shows that the present application also calculated p-values for pairwise t-tests of accessibility of addressable sites at four positions (P1-P4) across six-helix bundle variants (Del0, Del1, Del3). For most positions (P1 to P4), the differences in accessibility of addressable sites between six-helix bundle variants (Del0, Del1, Del3) are not statistically significant, as indicated by the higher p-values in the comparison. The t-tests indicate that the observed changes in average dark times between these deletion variants do not reach a significant level, suggesting that position-dependent accessibility can be relatively consistent across deletions, at least within the range of experimental conditions and statistical thresholds applied.

[0136] In addition, the present application calculated the Pearson correlation coefficient for each six-helix bundle to quantitatively describe the correlation between rigidity and accessibility. Figure 13A series of scatter plots are presented illustrating the relationship between rigidity (duration length) and site accessibility (localization frequency) for three different rigidities of six-helix bundle structures (Del0, Del1, and Del3). Each subplot is labeled accordingly. The specific analysis results are as follows:

[0137] For Del0, data points are densely distributed around the lower range of duration length, with a slight dispersion as length increases. The calculated Pearson correlation coefficient is -0.0454, indicating negligible negative correlation. 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 across a range of duration lengths. The correlation coefficient is 0.0295, indicating almost no positive correlation. The accompanying p-value of 0.6208 confirms the lack of statistical significance.

[0139] In the Del3 plot, data points remain comparably distributed, with a correlation coefficient of -0.0058, further confirming the lack of correlation. The p-value is 0.9219, indicating no significant statistical relationship.

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

[0141] Here, the null hypothesis in the hypothesis test is that there is no correlation between rigidity (duration length) and site accessibility (localization frequency). A low p-value (≤ 0.05) indicates strong evidence against the null hypothesis, suggesting that the observed data is unlikely to occur under the assumption of no correlation. Therefore, the correlation is considered statistically significant. A high p-value (> 0.05) indicates weak evidence against the null hypothesis, suggesting that the observed correlation is likely to occur randomly. In this case, the correlation is not statistically significant. In all three different rigidities of six-helix bundles, high p-values are shown, indicating that any correlation observed between duration length and localization frequency is likely due to random factors and there is no significant relationship between the two variables. This reinforces 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 method as described above, 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 the nucleic acid nanostructure by a microscope, and to preprocess to obtain spatial information and temporal information;

[0144] The quantitative evaluation module is used for quantitative evaluation of structure rigidity according to spatial information or quantitative evaluation of site accessibility according to time information;

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

[0146] It should be noted that the relational terms herein, such as first and second, and the like, are used solely to distinguish one from another entity or action without necessarily requiring or implying any actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0147] All documents mentioned in this application are incorporated herein by reference as if each individual document were specifically and individually incorporated by reference. In addition, it is to be understood that the application can be carried out by specifically different embodiments and that numerous modifications or changes can be devised by those skilled in the art without departing from the spirit and scope thereof as hereinafter claimed.

Claims

1. A method for analyzing properties of nucleic acid nanostructures, characterized in that: The method comprises the following steps: S1. The nucleic acid nanostructure comprises one nucleic acid nanobeam or a plurality of nucleic acid nanobeams connected by a linker. Single-molecule localization imaging data of the nucleic acid nanostructure is obtained by microscopy. The single-molecule localization imaging data is preprocessed to obtain data of the nucleic acid nanostructure; S2. Spatial information of the nucleic acid nanostructure is obtained from the data of the nucleic acid nanostructure. The spatial information comprises spatial coordinates of a plurality of addressable sites; S3. A contour curve of the nucleic acid nanostructure is determined according to the spatial information. The contour curve is divided into a plurality of chain segments. A chain segment length L is calculated by spatial coordinates of end points at both ends of the chain segment. An angle correlation cosθ(L) is calculated by unit vectors of two end points on the contour curve with a distance of L; S4. A persistence length P of the nucleic acid nanostructure when the chain segment length is L is calculated by a relationship between the chain segment length L and an average value <cosθ(L)> of the angle correlation when the chain segment length is L. A quantitative analysis of structural rigidity of the nucleic acid nanostructure is determined according to the persistence length P; S5. Data of the nucleic acid nanostructure is obtained. Time information of the nucleic acid nanostructure is obtained. A quantitative analysis of site accessibility of the nucleic acid nanostructure is determined; Without changing a natural state or environmental conditions of the nucleic acid nanostructure, a quantitative analysis of structural rigidity and a quantitative analysis of site accessibility are simultaneously performed at a molecular level according to the same single-molecule localization imaging data; S6. A correlation analysis of the structural rigidity and the site accessibility is performed; The structural rigidity comprises a deformation resistance of the nucleic acid nanostructure when subjected to an external force. The site accessibility comprises a contactability and operability of a specific sequence or domain on the nucleic acid nanostructure.

2. The method of claim 1, wherein, Step S1 further comprises: S1.

1. Point cloud data of fluorescent groups of a nucleic acid nanostructure sample is obtained by single-molecule localization microscopy; S1.

2. Poor-quality fluorescent sites are filtered out from the point cloud data. Drift correction is performed. A super-resolution reconstruction image of the nucleic acid nanostructure is obtained; S1.

3. Single-particle recognition is performed. Data of each nucleic acid nanostructure is obtained by a clustering algorithm and / or manual recognition. The data comprises spatial information and time information.

3. The method of claim 1, wherein, Step S3 further comprises: S3.

1. Spatial coordinates of N addressable sites on the nucleic acid nanostructure are obtained. A contour curve of the nucleic acid nanostructure is determined according to the spatial information; S3.

2. An interpolation algorithm is used. N addressable sites on the contour curve are increased to M end points. The chain segment is formed between each two end points, wherein M>N; S3.

3. A chain segment length L is calculated by spatial coordinates of end points at both ends of the chain segment. A unit vector is calculated by spatial coordinates of each end point and a previous adjacent end point on the contour curve. An angle correlation cosθ(L) is calculated by an inner product between unit vectors of two end points on the contour curve with a distance of L.

4. The method of claim 1, wherein, Step S4 further comprises: The relationship between the segment length L and the average value <cosθ(L)> of the angle correlation on the contour curve when the segment length is L includes a worm chain model; The formula of the worm chain model includes: <cosθ(L)> = e^(-L / (2P)), 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.

5. The method of claim 1, wherein, Further comprising: The morphology of the nucleic acid nanobeam includes a four-helix bundle, a six-helix bundle and an eight-helix bundle, and 4-16 addressable sites are distributed in the longitudinal direction of the nucleic acid nanobeam, and one or more single strands that can bind and dissociate with imaging probes are distributed on each addressable site.

6. The method of claim 1, wherein, Step S5 further comprises: S5.1 obtaining the data of the nucleic acid nanostructure by the method as described in step S1, and further obtaining the time information of the nucleic acid nanostructure; S5.2 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 localization frequency includes the number of times of binding and dissociation of the single strand and the imaging probe on the addressable site per unit time; and the binding and dissociation kinetics includes the analysis of the bright time and the dark time in the photodynamic fingerprint of the addressable site.

7. The method of claim 1, wherein, Step S6 further comprises: S6.1 in the same time, the first quantitative analysis of the structural rigidity of a plurality of nucleic acid nanostructures with different structural rigidity degrees but the same initial morphology is counted; S6.2 in the same time, the second quantitative analysis of the site accessibility of the nucleic acid nanostructure is counted; S6.3 the correlation between the structural rigidity and the site accessibility of the plurality of nucleic acid nanostructures is determined through the first quantitative analysis and the second quantitative analysis.

8. The method of claim 1, wherein, Step S6 further comprises: S6.1 in the same time, the persistence length P of three nucleic acid nanobeam with different structural rigidity degrees but the same initial morphology is counted; S6.2 in the same time, the localization frequency of the addressable sites on the nucleic acid nanobeam is counted, and the average dark time on four positions of the addressable sites is counted; S6.3 the average dark time on four positions of the addressable sites of three nucleic acid nanobeam is plotted as a box plot or subjected to t-test to obtain the position dependence, the Pearson correlation coefficient of the persistence length P and the localization frequency of three nucleic acid nanobeam is counted, and the correlation between the structural rigidity and the site accessibility is determined according to the position dependence and / or the Pearson correlation coefficient.

9. The method of claim 1, wherein, Step S6 further comprises: S6.1 comparative analysis of the accessibility of the addressable sites at different spatial positions on different rigid six-helix bundles is performed, and the average dark time is used to quantitatively describe the accessibility; S6.2 the Pearson correlation coefficient of each six-helix bundle is calculated to quantitatively describe the correlation between the rigidity and the accessibility.

10. A device for applying the method according to any one of claims 1 to 9, characterized in that The single-molecule localization module, the quantitative evaluation module and the data analysis module are included. The single-molecule localization module is used for acquiring single-molecule localization imaging data of a nucleic acid nanostructure by a microscope, and pre-processing to obtain spatial information and time information. The quantitative evaluation module is used for quantitatively evaluating structure rigidity according to the spatial information or quantitatively evaluating site accessibility according to the time information. The data analysis module further analyzes properties of the nucleic acid nanostructure or relationships between different properties according to the quantitatively evaluated data.

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