Method and system for obtaining single cell with precise spatial positioning by tissue slice

Abstract

The invention relates to the field of molecular cell biology, and discloses a method and system for obtaining a single cell with precise spatial localization through tissue section.The method comprises the steps that a fixing agent of a target tissue sample is prepared, the target tissue sample is fixed, tissue embedding is conducted on the fixed tissue sample, and the embedded tissue sample is sectioned; marking target mRNA molecules of the slice samples, constructing a sequencing library of the marked slice samples, and sequencing the marked slice samples to obtain single cell sequencing data; comparing the single cell sequencing data with a target gene corresponding to the target single cell, collecting image data of the slice sample, constructing a cell space trajectory of the target single cell, and determining spatial positioning of the target single cell; and constructing a cutting path of the slice sample, cutting the slice sample, constructing a pressure gradient environment of the cut sample, and separating the target single cell of the cut sample. According to the invention, the activity effect and purity of single cell acquisition can be improved.

Description

Technical Field

[0001] The present invention relates to a method and system for obtaining single cells with precise spatial positioning from tissue slices, and belongs to the field of molecular cell biology. Background Art

[0002] Single cell acquisition refers to the process of isolating individual cells from tissues for subsequent experimental analysis. Single cell acquisition is crucial for studying individual cell characteristics, gene expression, cell function, and cell heterogeneity.

[0003] At present, the traditional methods for obtaining single cells mainly include micromanipulation technology and enzymatic hydrolysis, which use microscopes and specific enzymes to obtain single cells. This method causes damage to the extracted single cells because specific enzymes will affect the activity and function of the cells, affecting subsequent single cell research and analysis.

[0004] Therefore, a solution is urgently needed to improve the activity and purity of single cell acquisition. Summary of the invention

[0005] The present invention provides a method and system for obtaining single cells with precise spatial positioning from tissue sections, the main purpose of which is to improve the activity effect and purity of single cell acquisition.

[0006] To achieve the above-mentioned purpose, the present invention provides a method for obtaining single cells with precise spatial positioning from tissue sections, comprising:

[0007] Obtaining a target tissue sample of a target single cell, preparing a fixative for the target tissue sample, fixing the target tissue sample based on the fixative to obtain a fixed tissue sample, embedding the fixed tissue sample with a preset resin to obtain an embedded tissue sample, and slicing the embedded tissue sample to obtain a slice sample;

[0008] Obtaining a spatial transcriptome chip of the slice sample, labeling the target mRNA molecule of the slice sample using a probe corresponding to the spatial transcriptome chip to obtain a labeled slice sample, constructing a sequencing library of the labeled slice sample, and sequencing the labeled slice sample based on the sequencing library using a preset sequencing algorithm to obtain single-cell sequencing data;

[0009] The single-cell sequencing data is compared with the target gene corresponding to the target single cell to obtain the gene data of the barcode corresponding to the probe, the image data of the slice sample is collected, and based on the image data and the gene data, a preset virtual space algorithm is used to construct the cell space trajectory of the target single cell, and the spatial location of the target single cell is determined according to the cell space trajectory;

[0010] According to the spatial positioning, a cutting path of the sliced ​​sample is constructed using a preset path planning algorithm, and based on the cutting path, the sliced ​​sample is cut using a preset laser cutter to obtain a cut sample;

[0011] A pressure gradient environment is constructed for the cut sample, and based on the pressure gradient environment, target single cells of the cut sample are separated.

[0012] Optionally, the fixing agent for preparing the target tissue sample comprises:

[0013] preparing fixative materials and buffer materials for the target tissue sample;

[0014] Based on the configuration material, a buffer solution of the target tissue sample is configured;

[0015] determining a buffer solution concentration and a buffer solution volume of the buffer solution;

[0016] calculating the material mass of the fixative material according to the buffer solution concentration and the buffer solution volume;

[0017] A fixative for the target tissue sample is configured according to the material mass, the buffer solution and the fixative material.

[0018] Optionally, embedding the fixed tissue sample with a preset resin to obtain the embedded tissue sample includes:

[0019] preparing a dehydration solvent for the fixed tissue sample, and dehydrating the fixed tissue sample based on the dehydration solvent to obtain a dehydrated tissue sample;

[0020] Determining a transparent solvent for the dehydrated tissue sample, and using the transparent solvent to make the dehydrated tissue sample transparent to obtain a transparent tissue sample;

[0021] Using the resin to infiltrate the transparent tissue sample to obtain an infiltrated tissue sample;

[0022] An embedding mold for the infiltrated tissue sample is determined, and the infiltrated tissue sample is embedded according to the embedding mold to obtain an embedded tissue sample.

[0023] Optionally, constructing a sequencing library of the labeled slice sample comprises:

[0024] Extracting target DNA of target single cells corresponding to the labeled slice sample;

[0025] Constructing a PCR amplification environment for the target DNA, and amplifying the target DNA based on the PCR amplification environment to obtain amplified DNA;

[0026] Repairing the ends of the amplified DNA, and adding an A tail of the amplified DNA based on the ends;

[0027] According to the A tail, determining a sequencing adapter to be connected to the amplified DNA;

[0028] Connecting the sequencing adapter and the amplified DNA to obtain a specific DNA fragment;

[0029] A sequencing library of the labeled slice sample is constructed based on the specific DNA fragment.

[0030] Optionally, constructing the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm includes:

[0031] Extracting image features of the image data, and registering the image data based on the image features to obtain registration data;

[0032] Constructing a three-dimensional spatial model of the slice sample corresponding to the image data according to the registration data;

[0033] Determining the physical distance between cells of the sliced ​​tissue according to the three-dimensional spatial model;

[0034] Determining a cell identifier and a cell gene expression value of the slice sample according to the gene data;

[0035] Determine the pseudo-space-time distance of cells of the slice sample using the virtual space algorithm according to the cell identifier and the cell gene expression value;

[0036] The comprehensive spatial distance is calculated according to the cell physical distance and the cell pseudo-spatiotemporal distance.

[0037] According to the comprehensive spatial distance, the cell spatial trajectory of the target single cell is determined.

[0038] Optionally, registering the image data based on the image features to obtain registration data includes:

[0039] A feature matching algorithm is defined for the image features, and based on the feature matching algorithm, original feature points and matching feature points of the image data are determined;

[0040] constructing an image transformation model of the image data according to the original feature points;

[0041] Determining the objective function of the image transformation model according to the original feature points and the matching feature points,

[0042] Calculating optimal transformation parameters of the image transformation model according to the objective function;

[0043] Registration data of the image data is determined according to the optimal transformation parameters.

[0044] Optionally, constructing a cutting path for the slice sample using a preset path planning algorithm according to the spatial positioning includes:

[0045] Determining a cutting start point and a cutting end point of the slice sample according to the spatial positioning;

[0046] Analyzing the cell structure and cell distribution status of the slice sample;

[0047] Determining cutting constraints of the slice sample according to the cell structure and the cell distribution state;

[0048] Analyzing the tissue properties of the slice sample, and determining the cutting parameters of the slice sample according to the tissue properties;

[0049] According to the cutting constraint conditions and the cutting parameters, using the path planning algorithm, determining an initial cutting path from the cutting start point to the cutting end point;

[0050] The feasibility of the initial cutting path is verified, and when the feasibility meets a preset feasibility threshold, the initial cutting path is used as the cutting path of the slice sample.

[0051] Optionally, based on the cutting path, cutting the sliced ​​sample using a preset laser cutter to obtain a cut sample includes:

[0052] Precision calibrating the laser cutter to obtain a calibrated laser cutter;

[0053] Determining the laser power, cutting speed and cutting depth of the calibration laser cutter according to the cutting path;

[0054] Analyzing a cutting path of the calibration laser cutter according to the laser power, the cutting speed, and the cutting depth;

[0055] constructing a cutting path monitoring module for the calibration laser cutter according to the analyzed cutting path and the cutting path;

[0056] Based on the cutting path monitoring module, the sliced ​​sample is cut to obtain a cut sample.

[0057] Optionally, constructing the pressure gradient environment of the cut sample comprises:

[0058] Determining the microfluidic chip of the cut sample, and constructing the channel layout of the microfluidic chip;

[0059] According to the channel layout, configuring a pressure controller of the microfluidic chip;

[0060] Analyzing the separation requirements of the cut sample, and determining the pressure gradient parameters of the cut sample according to the separation requirements;

[0061] A pressure gradient environment of the cut sample is constructed according to the pressure gradient parameter and the pressure controller.

[0062] In order to solve the above problems, the present invention also provides a system for obtaining single cells with precise spatial positioning from tissue sections, the system comprising:

[0063] A tissue slicing module is used to obtain a target tissue sample of a target single cell, configure a fixative for the target tissue sample, fix the target tissue sample based on the fixative to obtain a fixed tissue sample, embed the fixed tissue sample with a preset resin to obtain an embedded tissue sample, and slice the embedded tissue sample to obtain a slice sample;

[0064] A sample sequencing module is used to obtain the spatial transcriptome chip of the slice sample, label the target mRNA molecule of the slice sample using the corresponding probe of the spatial transcriptome chip to obtain the labeled slice sample, construct a sequencing library of the labeled slice sample, and sequence the labeled slice sample based on the sequencing library using a preset sequencing algorithm to obtain single-cell sequencing data;

[0065] A cell positioning module is used to compare the single-cell sequencing data with the target gene corresponding to the target single cell, obtain the gene data of the barcode corresponding to the probe, collect the image data of the slice sample, and construct the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm, and determine the spatial positioning of the target single cell according to the cell space trajectory;

[0066] A laser cutting module, configured to construct a cutting path for the sliced ​​sample using a preset path planning algorithm according to the spatial positioning, and cut the sliced ​​sample using a preset laser cutter based on the cutting path to obtain a cut sample;

[0067] The single cell acquisition module is used to construct a pressure gradient environment for the cut sample, and to separate the target single cell of the cut sample based on the pressure gradient environment.

[0068] The embodiment of the present invention can quickly penetrate cells by configuring the fixative of the target tissue sample, cross-link with proteins and other biomacromolecules in the cells, thereby maintaining the morphology and structure of the cells, so that they will not change significantly during subsequent processing and observation; optionally, the embodiment of the present invention can provide spatial distribution information of gene expression by obtaining the spatial transcriptome chip of the slice sample, that is, which genes are expressed at specific locations on the tissue slice, which is helpful for understanding the spatial organization and function of cells in the tissue; the embodiment of the present invention can obtain single-cell sequencing data by sequencing the labeled slice sample based on the sequencing library using a preset sequencing algorithm, and can obtain high-precision gene expression quantification through high-depth sequencing. data; the embodiment of the present invention constructs the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm, which can visualize the dynamic behavior of the cell and understand how cells interact and coordinate in the process of tissue formation and organ development; the embodiment of the present invention constructs the cutting path of the slice sample according to the spatial positioning using a preset path planning algorithm, which can reduce damage to non-target areas of the sample by optimizing the cutting path, improve the accuracy and efficiency of the cutting, and finally, the embodiment of the present invention separates the target single cell of the cut sample based on the pressure gradient environment, which can effectively separate the target single cell from other cells and impurities, thereby improving the purity of the separation. Therefore, the method and system for obtaining single cells with precise spatial positioning in tissue slices provided by the embodiment of the present invention can improve the activity effect and purity of single cell acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 A schematic diagram of a process for obtaining single cells with precise spatial localization from tissue slices provided by an embodiment of the present invention;

[0070] Figure 2 A schematic diagram of a module for implementing the method of obtaining single cells with precise spatial localization from tissue sections provided in one embodiment of the present invention.

[0071] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0072] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0073] The embodiment of the present application provides a method for obtaining single cells with precise spatial positioning from tissue sections. The execution subject of the method for obtaining single cells with precise spatial positioning from tissue sections includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for obtaining single cells with precise spatial positioning from tissue sections can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0074] Embodiment 1:

[0075] Reference Figure 1 FIG. 1 is a flow chart of a method for obtaining single cells with precise spatial localization from tissue slices provided by an embodiment of the present invention. In this embodiment, the method for obtaining single cells with precise spatial localization from tissue slices includes:

[0076] S1. Obtain a target tissue sample of a target single cell, prepare a fixative for the target tissue sample, fix the target tissue sample based on the fixative to obtain a fixed tissue sample, embed the fixed tissue sample with a preset resin to obtain an embedded tissue sample, and slice the embedded tissue sample to obtain a slice sample.

[0077] In the embodiment of the present invention, the target single cell can be obtained by obtaining a target tissue sample of the target single cell through a single cell separation technology, wherein the target tissue sample refers to a small portion of tissue taken from an organism and containing the target single cell.

[0078] The embodiment of the present invention can quickly penetrate cells by configuring the fixative of the target tissue sample, cross-link with proteins and other biomacromolecules in the cells, thereby maintaining the morphology and structure of the cells, so that they will not change significantly during subsequent processing and observation. The fixative refers to a chemical substance used for processing biological tissue samples, maintaining the integrity of cell and tissue structures, preventing tissue corruption, and preparing for subsequent experimental steps.

[0079] As an embodiment of the present invention, the fixing agent for preparing the target tissue sample includes:

[0080] preparing fixative materials and buffer materials for the target tissue sample;

[0081] Based on the configuration material, a buffer solution of the target tissue sample is configured;

[0082] determining a buffer solution concentration and a buffer solution volume of the buffer solution;

[0083] calculating the material mass of the fixative material according to the buffer solution concentration and the buffer solution volume;

[0084] A fixative for the target tissue sample is configured according to the material mass, the buffer solution and the fixative material.

[0085] Among them, the fixative material refers to the specific chemical substance required for preparing the tissue sample fixative. The buffer material refers to the chemical substance used to prepare the buffer solution. The buffer solution refers to a chemical solution that has the ability to resist changes in pH value and is used to maintain the pH value of the solution within a relatively stable range. The buffer solution concentration refers to the concentration of buffer salts in the buffer system used to adjust pH. The buffer solution volume refers to the total amount of buffer configured. The material mass refers to the mass of the specific chemical substance required when preparing the fixative.

[0086] In the embodiment of the present invention, the target tissue sample is fixed based on the fixative to obtain a fixed tissue sample, which can stabilize proteins and other macromolecules in the cell and prevent them from displacement or degradation during subsequent processing (such as dehydration, transparency and embedding). The fixed tissue sample refers to a biological tissue sample treated with a fixative.

[0087] In the embodiment of the present invention, the fixed tissue sample is embedded with a preset resin to provide a hard matrix for the embedded tissue sample, making it easier to thinly slice the tissue sample, thereby obtaining a slice suitable for microscopic observation. The preset resin refers to a synthetic or natural polymer material used for embedding fixed tissue samples in histological research. The embedded tissue sample refers to a tissue sample that has been fixed, dehydrated, and transparentized.

[0088] As an embodiment of the present invention, embedding the fixed tissue sample with a preset resin to obtain the embedded tissue sample includes:

[0089] preparing a dehydration solvent for the fixed tissue sample, and dehydrating the fixed tissue sample based on the dehydration solvent to obtain a dehydrated tissue sample;

[0090] Determining a transparent solvent for the dehydrated tissue sample, and using the transparent solvent to make the dehydrated tissue sample transparent to obtain a transparent tissue sample;

[0091] Using the resin to infiltrate the transparent tissue sample to obtain an infiltrated tissue sample;

[0092] An embedding mold for the infiltrated tissue sample is determined, and the infiltrated tissue sample is embedded according to the embedding mold to obtain an embedded tissue sample.

[0093] Wherein, the dehydrating solvent refers to a chemical substance used to remove water from a tissue sample to facilitate the subsequent transparent and embedding steps, such as ethanol, acetone, etc. The dehydrated tissue sample refers to a tissue block after dehydration treatment, that is, a tissue sample in which water is removed by using a dehydrating solvent (such as ethanol or acetone) to facilitate the subsequent transparent, infiltration and embedding steps. The transparent solvent refers to a chemical substance used to replace the dehydrating agent (such as ethanol or acetone) in the dehydrated tissue sample, so that the tissue sample becomes transparent and facilitates light to pass through, so as to facilitate subsequent microscopic observation, such as xylene, benzene, etc. The transparent tissue sample refers to a tissue block after transparent treatment. The infiltrated tissue sample refers to a tissue block that is completely infiltrated with resin. The embedding mold refers to a container or device used to hold and shape the resin or other embedding medium used in the embedding process of the tissue sample.

[0094] The embodiment of the present invention can minimize the deformation and damage of the tissue during the cutting process and maintain the integrity of the tissue by slicing the embedded tissue sample to obtain the sliced ​​sample. The sliced ​​sample refers to a thin layer of tissue slice obtained by cutting the embedded tissue sample with a slicer.

[0095] S2. Obtain the spatial transcriptome chip of the slice sample, use the corresponding probe of the spatial transcriptome chip to label the target mRNA molecule of the slice sample to obtain a labeled slice sample, construct a sequencing library of the labeled slice sample, and based on the sequencing library, use a preset sequencing algorithm to sequence the labeled slice sample to obtain single-cell sequencing data.

[0096] The spatial transcriptome chip of the slice sample can provide spatial distribution information of gene expression, that is, which genes are expressed at specific locations on the tissue slice, which helps to understand the spatial organization and function of cells in the tissue. The spatial transcriptome chip refers to a high-tech product that integrates microarray or high-throughput sequencing technology, which can realize spatial analysis of gene expression information on tissue slices.

[0097] The embodiment of the present invention uses the corresponding probe of the spatial transcriptome chip to label the target mRNA molecule of the slice sample, so that the labeled slice sample can identify and quantify the mRNA molecule at a specific position on the tissue slice, thereby revealing the spatial distribution and pattern of gene expression. Among them, the target mRNA molecule refers to a type of RNA in the target single cell, which plays a key role in the process of gene expression. The labeled slice sample refers to a tissue slice processed by a specific labeling technology, and the specific molecules (such as mRNA) on these slices have been labeled with specific markers (such as fluorescent dyes, enzymes, quantum dots, etc.).

[0098] As an embodiment of the present invention, the target mRNA molecules of the slice sample are labeled with the corresponding probes of the spatial transcriptomics chip, and the labeled slice sample can be labeled by spatial transcriptomics technology.

[0099] The embodiment of the present invention can simultaneously detect tens of thousands of mRNA molecules by constructing a sequencing library of the labeled slice sample, thereby achieving high-throughput gene expression analysis and improving experimental efficiency and data volume. The sequencing library refers to a collection of DNA or RNA samples processed through specific experimental steps.

[0100] As an embodiment of the present invention, the construction of the sequencing library of the labeled slice sample includes:

[0101] Extracting target DNA of target single cells corresponding to the labeled slice sample;

[0102] Constructing a PCR amplification environment for the target DNA, and amplifying the target DNA based on the PCR amplification environment to obtain amplified DNA;

[0103] Repairing the ends of the amplified DNA, and adding an A tail of the amplified DNA based on the ends;

[0104] According to the A tail, determining a sequencing adapter to be connected to the amplified DNA;

[0105] Connecting the sequencing adapter and the amplified DNA to obtain a specific DNA fragment;

[0106] A sequencing library of the labeled slice sample is constructed based on the specific DNA fragment.

[0107] Wherein, the target DNA refers to a specific DNA molecule extracted from a single cell. The PCR amplification environment refers to the experimental conditions and technical settings for polymerase chain reaction. The amplified DNA refers to the DNA molecule amplified by the polymerase chain reaction (PCR) technology. The end refers to the end of the DNA molecule, that is, the linear end of the molecule or the 3' and 5' hydroxyl (OH) ends. The A tail refers to a string of adenylic acid (A) residues added to the 3' end of the DNA molecule. The sequencing adapter refers to a short, synthetic DNA molecule used to connect to the DNA fragment in the sequencing library for sequencing on a sequencer. The specific DNA fragment refers to a DNA fragment selected, amplified and prepared for high-throughput sequencing during the construction of the sequencing library.

[0108] Optionally, the repairing of the ends of the amplified DNA may be performed by using an end repair enzyme.

[0109] The embodiment of the present invention obtains single-cell sequencing data by sequencing the labeled slice sample based on the sequencing library using a preset sequencing algorithm, and can obtain high-precision gene expression quantitative data through high-depth sequencing. Wherein, the preset sequencing algorithm refers to a series of calculation steps and rules designed to identify and analyze DNA sequences from the raw image data generated by the sequencer. The single-cell sequencing data refers to detailed data on the genetic information of a single cell obtained by single-cell sequencing technology.

[0110] S3. Compare the single-cell sequencing data with the target gene corresponding to the target single cell to obtain the gene data of the barcode corresponding to the probe, collect the image data of the slice sample, and based on the image data and the gene data, use a preset virtual space algorithm to construct the cell space trajectory of the target single cell, and determine the spatial positioning of the target single cell according to the cell space trajectory.

[0111] The embodiment of the present invention can accurately quantify the expression level of the target gene in a single cell by comparing the single-cell sequencing data with the target gene corresponding to the target single cell, and provide data support for studying gene regulatory networks and signal pathways. The gene data refers to the detailed information about the gene expression in a single cell obtained by single-cell sequencing technology.

[0112] Optionally, as an embodiment of the present invention, the single-cell sequencing data is compared with the target gene corresponding to the target single cell, and the gene data of the barcode corresponding to the probe can be analyzed by sequence alignment and barcode splitting.

[0113] The embodiment of the present invention can intuitively understand the three-dimensional layout of the tissue structure and the spatial relationship of cells in the tissue by collecting the image data of the slice sample. The image data refers to the visual information about the slice sample obtained by microscope imaging technology, scanner or other imaging equipment.

[0114] The embodiment of the present invention can visualize the dynamic behavior of cells and understand how cells interact and coordinate during tissue formation and organ development by constructing the cell space trajectory of the target single cell based on the image data and the gene data and using a preset virtual space algorithm. The cell space trajectory refers to a record of the position and movement path of a single cell or a group of cells over time in a three-dimensional space.

[0115] As an embodiment of the present invention, constructing the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm includes:

[0116] Extracting image features of the image data, and registering the image data based on the image features to obtain registration data;

[0117] Constructing a three-dimensional spatial model of the slice sample corresponding to the image data according to the registration data;

[0118] Determining the physical distance between cells of the sliced ​​tissue according to the three-dimensional spatial model;

[0119] Determining a cell identifier and a cell gene expression value of the slice sample according to the gene data;

[0120] Determine the pseudo-space-time distance of cells of the slice sample using the virtual space algorithm according to the cell identifier and the cell gene expression value;

[0121] S=W×Q+D×(1-W) According to the cell physical distance and the cell pseudo-space-time distance, the comprehensive spatial distance is calculated using the following formula:

[0122] Among them, represents S comprehensive spatial distance, W represents the weight of cell pseudo-spacetime distance, Q represents cell pseudo-spacetime distance, and D represents cell physical distance.

[0123] According to the comprehensive spatial distance, the cell spatial trajectory of the target single cell is determined.

[0124] Among them, the image feature refers to the attribute that can represent the image content extracted from the image data. The registration data refers to the data obtained through the image registration process, which contains the information required to align two or more images. The three-dimensional space model refers to a mathematical or digital representation constructed in a three-dimensional coordinate system, which is used to simulate and describe the shape, size, position and relationship of objects, structures or phenomena in the real world. The cell physical distance refers to the actual distance measurement between two cells in three-dimensional space. The cell identifier refers to a mark or code used to uniquely identify a single cell. The cell gene expression value refers to the relative number or abundance of transcripts (such as mRNA) of a gene. The cell pseudo-space-time distance refers to the relative position relationship between different cells in a pseudo-space-time trajectory constructed based on single-cell sequencing data. The comprehensive spatial distance refers to a measurement that combines cell physical distance and cell pseudo-space-time distance, which more comprehensively describes the relative position and relationship of cells in space and time.

[0125] Optionally, registering the image data based on the image features to obtain registration data includes:

[0126] A feature matching algorithm is defined for the image features, and based on the feature matching algorithm, original feature points and matching feature points of the image data are determined;

[0127] B(u)=X(uc)+p+c constructs an image transformation model of the image data according to the original feature points, wherein the image transformation model includes:

[0128] Among them, B(u) represents the transformed position, u represents the original feature point corresponding to the image data, X represents the rotation matrix, c represents the rotation center corresponding to the image data, and p represents the translation vector;

[0129] Determine the objective function of the image transformation model according to the original feature points and the matching feature points, wherein the objective function includes:

[0130]

[0131] Among them, M(X, p) represents the objective function, X represents the rotation matrix, p represents the translation vector, and B(u i ) represents the transformed position of the original feature point corresponding to the i-th image data, v i represents the matching feature point corresponding to the i-th original feature point,

[0132] Calculating optimal transformation parameters of the image transformation model according to the objective function;

[0133] Registration data of the image data is determined according to the optimal transformation parameters.

[0134] Among them, the feature matching algorithm refers to a set of calculation methods for identifying and matching similar feature points in two images. The original feature point refers to a representative point identified by a feature detection algorithm in an image. The matching feature point refers to a feature point corresponding to the original feature point found in another image corresponding to the image where the original feature point is located. The image transformation model refers to a mathematical model that describes how to map an image to the corresponding position of another image through geometric transformation. The rotation matrix refers to a special square matrix used to describe the rotation of an object or coordinate system in three-dimensional space. The translation vector refers to a mathematical vector used to describe the translation of a point or object in space in a geometric transformation. The objective function refers to a mathematical function used to evaluate the quality of a solution in an optimization problem. The optimal transformation parameters refer to a set of parameters obtained by optimizing the objective function during the image registration process.

[0135] Optionally, the feature matching algorithm for defining the image features may be defined by a deep learning method.

[0136] The embodiment of the present invention can determine the spatial location of the target single cell according to the cell spatial trajectory, and lay a foundation for subsequent extraction of single cells through precise positioning. Wherein, the spatial positioning refers to determining the specific position of the target single cell in three-dimensional space.

[0137] S4. According to the spatial positioning, a cutting path of the sliced ​​sample is constructed using a preset path planning algorithm. Based on the cutting path, the sliced ​​sample is cut using a preset laser cutter to obtain a cut sample.

[0138] The embodiment of the present invention can optimize the cutting path by constructing the cutting path of the slice sample using a preset path planning algorithm according to the spatial positioning, thereby reducing damage to non-target areas of the sample and improving the accuracy and efficiency of cutting. The preset path planning algorithm refers to a set of computing programs or instruction sets designed to complete specific tasks (such as cutting, scanning, printing, etc.). The cutting path refers to a predetermined route or trajectory for cutting on a slice sample (such as a tissue slice, a cell slice, etc.).

[0139] As an embodiment of the present invention, constructing a cutting path of the slice sample using a preset path planning algorithm according to the spatial positioning includes:

[0140] Determining a cutting start point and a cutting end point of the slice sample according to the spatial positioning;

[0141] Analyzing the cell structure and cell distribution status of the slice sample;

[0142] Determining cutting constraints of the slice sample according to the cell structure and the cell distribution state;

[0143] Analyzing the tissue properties of the slice sample, and determining the cutting parameters of the slice sample according to the tissue properties;

[0144] According to the cutting constraint conditions and the cutting parameters, using the path planning algorithm, determining an initial cutting path from the cutting start point to the cutting end point;

[0145] The feasibility of the initial cutting path is verified, and when the feasibility meets a preset feasibility threshold, the initial cutting path is used as the cutting path of the slice sample.

[0146] Among them, the cutting starting point refers to the specific position point where the cutting tool starts cutting when cutting the slice sample. The cutting end point refers to the specific position point where the cutting tool completes cutting when cutting the slice sample. The cell structure refers to the intercellular connection characteristics of the slice sample. The cell distribution state refers to the arrangement, density, spatial relationship and organizational form of cells in the tissue or sample. The cutting constraint condition refers to a series of restrictions and requirements that need to be followed when cutting the slice sample. These conditions ensure that the cutting process will not destroy the structural integrity of the sample, will not affect the subsequent experimental analysis, and can meet specific research needs. The tissue properties refer to the physical and biological properties of the slice sample, which affect the selection of cutting parameters and the design of the cutting process. The cutting parameters refer to a series of parameters that need to be set during the tissue section or sample cutting process. The initial cutting path refers to the cutting route taken by the cutting tool for the first time according to the preset path planning when cutting the slice sample. The feasibility refers to the possibility of whether the cutting path can be successfully executed in actual operation. The preset feasibility threshold refers to a series of quantitative standards set to judge whether the solution is acceptable when implementing the cutting path planning or other technical solutions.

[0147] Optionally, the cutting parameters of the sliced ​​sample determined according to the tissue properties may be determined by finite element analysis.

[0148] The embodiment of the present invention uses a preset laser cutter to cut the slice sample based on the cutting path, so that the cut sample can have a small heat-affected area, reduce thermal damage to the tissue around the sample, and maintain the integrity of the cell structure. The laser cutter refers to a device that uses the energy of a laser beam to cut a material. The cut sample refers to a tissue or material sample that has been processed by the laser cutter according to the preset cutting path.

[0149] As an embodiment of the present invention, the cutting path is based on which the sliced ​​sample is cut using a preset laser cutter to obtain a cut sample, including:

[0150] Precision calibrating the laser cutter to obtain a calibrated laser cutter;

[0151] Determining the laser power, cutting speed and cutting depth of the calibration laser cutter according to the cutting path;

[0152] Analyzing a cutting path of the calibration laser cutter according to the laser power, the cutting speed, and the cutting depth;

[0153] constructing a cutting path monitoring module for the calibration laser cutter according to the analyzed cutting path and the cutting path;

[0154] Based on the cutting path monitoring module, the sliced ​​sample is cut to obtain a cut sample.

[0155] Among them, the calibrated laser cutter refers to a laser cutting device that has undergone a series of precise adjustments and optimization processes to ensure that its cutting accuracy and performance meet the specified standards. The laser power refers to the power of the laser beam emitted by the laser cutter during the cutting process. The cutting speed refers to the speed at which the laser beam moves relative to the material when the laser cutter cuts the material. The cutting depth refers to the depth to which the laser beam acts on the surface of the material and penetrates the material during the laser cutting process. The analyzed cutting path refers to the cutting route predicted by a series of calculations and analyses. The cutting path monitoring module refers to a hardware and software component integrated in the cutting system, the purpose of which is to monitor and control the movement path of the cutting tool (such as a laser beam, a tool, etc.) in real time during the cutting process.

[0156] S5. Construct a pressure gradient environment for the cut sample, and separate target single cells of the cut sample based on the pressure gradient environment.

[0157] The embodiment of the present invention can help improve the purity of target cells and reduce the interference of non-target cells by constructing the pressure gradient environment of the cut sample. The pressure gradient environment refers to a pressure change area along the flow direction of the fluid formed by accurately controlling the pressure difference.

[0158] As an embodiment of the present invention, the step of constructing a pressure gradient environment of the cut sample includes:

[0159] Determining the microfluidic chip of the cut sample, and constructing the channel layout of the microfluidic chip;

[0160] According to the channel layout, configuring a pressure controller of the microfluidic chip;

[0161] Analyzing the separation requirements of the cut sample, and determining the pressure gradient parameters of the cut sample according to the separation requirements;

[0162] A pressure gradient environment of the cut sample is constructed according to the pressure gradient parameter and the pressure controller.

[0163] Among them, the microfluidic chip refers to a device for manipulating and controlling the flow of tiny fluids. The channel layout refers to the fluid channel network designed and arranged on the microfluidic chip, which determines the flow path, direction, speed and possible interactions of the fluid in the chip. The pressure controller refers to a device for regulating and maintaining the pressure in a fluid system within a set range. The separation requirement refers to the goal and conditions for the separation of target single cells in the sample after cutting. The pressure gradient parameter refers to a parameter related to the pressure gradient set in order to achieve a specific separation or fluid operation.

[0164] The embodiment of the present invention can effectively separate the target single cell from other cells and impurities by separating the target single cell of the cut sample based on the pressure gradient environment, thereby improving the purity of the separation.

[0165] The embodiment of the present invention can quickly penetrate cells by configuring the fixative of the target tissue sample, cross-link with proteins and other biomacromolecules in the cells, thereby maintaining the morphology and structure of the cells, so that they will not change significantly during subsequent processing and observation; optionally, the embodiment of the present invention can provide spatial distribution information of gene expression by obtaining the spatial transcriptome chip of the slice sample, that is, which genes are expressed at specific locations on the tissue slice, which is helpful for understanding the spatial organization and function of cells in the tissue; the embodiment of the present invention can obtain single-cell sequencing data by sequencing the labeled slice sample based on the sequencing library using a preset sequencing algorithm, and can obtain high-precision gene expression quantification through high-depth sequencing. data; the embodiment of the present invention constructs the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm, which can visualize the dynamic behavior of the cell and understand how cells interact and coordinate in the process of tissue formation and organ development; the embodiment of the present invention constructs the cutting path of the slice sample according to the spatial positioning using a preset path planning algorithm, which can reduce damage to non-target areas of the sample by optimizing the cutting path, improve the accuracy and efficiency of the cutting, and finally, the embodiment of the present invention separates the target single cell of the cut sample based on the pressure gradient environment, which can effectively separate the target single cell from other cells and impurities, thereby improving the purity of the separation. Therefore, the method and system for obtaining single cells with precise spatial positioning in tissue slices provided by the embodiment of the present invention can improve the activity effect and purity of single cell acquisition.

[0166] Embodiment 2:

[0167] like Figure 2 Shown is a functional module diagram of a single-cell system for obtaining tissue slices with precise spatial positioning according to the present invention.

[0168] The tissue slice acquisition with precise spatial positioning single cell system 200 of the present invention can be installed in an electronic device. According to the functions to be implemented, the tissue slice acquisition with precise spatial positioning single cell system can include a tissue slice module 201, a sample sequencing module 202, a cell positioning module 203, a laser cutting module 204 and a single cell acquisition module 205. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0169] In the embodiment of the present invention, the functions of each module / unit are as follows:

[0170] The tissue slicing module 201 is used to obtain a target tissue sample of a target single cell, configure a fixative for the target tissue sample, fix the target tissue sample based on the fixative to obtain a fixed tissue sample, embed the fixed tissue sample with a preset resin to obtain an embedded tissue sample, and slice the embedded tissue sample to obtain a slice sample;

[0171] The sample sequencing module 202 is used to obtain the spatial transcriptome chip of the slice sample, label the target mRNA molecule of the slice sample using the corresponding probe of the spatial transcriptome chip to obtain the labeled slice sample, construct a sequencing library of the labeled slice sample, and sequence the labeled slice sample based on the sequencing library using a preset sequencing algorithm to obtain single-cell sequencing data;

[0172] The cell positioning module 203 is used to compare the single-cell sequencing data with the target gene corresponding to the target single cell, obtain the gene data of the barcode corresponding to the probe, collect the image data of the slice sample, and construct the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm, and determine the spatial positioning of the target single cell according to the cell space trajectory;

[0173] The laser cutting module 204 is used to construct a cutting path for the slice sample according to the spatial positioning using a preset path planning algorithm, and based on the cutting path, cut the slice sample using a preset laser cutter to obtain a cut sample;

[0174] The single cell acquisition module 205 is used to construct a pressure gradient environment for the cut sample, and separate the target single cells of the cut sample based on the pressure gradient environment.

[0175] In detail, the modules in the tissue slice acquisition with precise spatial positioning single cell system 200 in the embodiment of the present invention are used in the same manner as described above. Figure 1 The tissue section acquisition with precise spatial positioning of single cells described in the previous section uses the same technical means and can produce the same technical effects, which will not be repeated here.

[0176] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for obtaining single cells with precise spatial positioning in tissue sections, characterized in that: The method comprises: Obtaining a target tissue sample of a target single cell, preparing a fixative for the target tissue sample, fixing the target tissue sample based on the fixative to obtain a fixed tissue sample, embedding the fixed tissue sample with a preset resin to obtain an embedded tissue sample, and slicing the embedded tissue sample to obtain a slice sample; Obtaining a spatial transcriptome chip of the slice sample, labeling the target mRNA molecule of the slice sample using a probe corresponding to the spatial transcriptome chip to obtain a labeled slice sample, constructing a sequencing library of the labeled slice sample, and sequencing the labeled slice sample based on the sequencing library using a preset sequencing algorithm to obtain single-cell sequencing data; The single-cell sequencing data is compared with the target gene corresponding to the target single cell to obtain the gene data of the barcode corresponding to the probe, the image data of the slice sample is collected, and based on the image data and the gene data, a preset virtual space algorithm is used to construct the cell space trajectory of the target single cell, and the spatial location of the target single cell is determined according to the cell space trajectory; According to the spatial positioning, a cutting path of the sliced ​​sample is constructed using a preset path planning algorithm, and based on the cutting path, the sliced ​​sample is cut using a preset laser cutter to obtain a cut sample; A pressure gradient environment is constructed for the cut sample, and based on the pressure gradient environment, target single cells of the cut sample are separated.

2. The method for obtaining single cells with precise spatial positioning from tissue sections as claimed in claim 1, characterized in that: The fixing agent for preparing the target tissue sample comprises: preparing fixative materials and buffer materials for the target tissue sample; Based on the configuration material, a buffer solution of the target tissue sample is configured; Determining a buffer solution concentration and a buffer solution volume of the buffer solution; calculating the material mass of the fixative material according to the concentration of the buffer solution and the volume of the buffer solution; A fixative for the target tissue sample is configured according to the material mass, the buffer solution and the fixative material.

3. The method for obtaining single cells with precise spatial positioning from tissue sections as claimed in claim 1, characterized in that: The method of embedding the fixed tissue sample with a preset resin to obtain the embedded tissue sample comprises: preparing a dehydration solvent for the fixed tissue sample, and dehydrating the fixed tissue sample based on the dehydration solvent to obtain a dehydrated tissue sample; Determining a transparent solvent for the dehydrated tissue sample, and using the transparent solvent to make the dehydrated tissue sample transparent to obtain a transparent tissue sample; Using the resin to infiltrate the transparent tissue sample to obtain an infiltrated tissue sample; An embedding mold for the infiltrated tissue sample is determined, and the infiltrated tissue sample is embedded according to the embedding mold to obtain an embedded tissue sample.

4. The method for obtaining single cells with precise spatial positioning from tissue sections as claimed in claim 1, characterized in that: The step of constructing a sequencing library of the labeled slice sample comprises: Extracting target DNA of target single cells corresponding to the labeled slice sample; Constructing a PCR amplification environment for the target DNA, and amplifying the target DNA based on the PCR amplification environment to obtain amplified DNA; Repairing the ends of the amplified DNA, and adding an A tail of the amplified DNA based on the ends; According to the A tail, determining a sequencing adapter to be connected to the amplified DNA; Connecting the sequencing adapter and the amplified DNA to obtain a specific DNA fragment; A sequencing library of the labeled slice sample is constructed based on the specific DNA fragment.

5. The method for obtaining single cells with precise spatial positioning from tissue sections as claimed in claim 1, characterized in that: The method of constructing the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm includes: Extracting image features of the image data, and registering the image data based on the image features to obtain registration data; Constructing a three-dimensional spatial model of the slice sample corresponding to the image data according to the registration data; Determining the physical distance between cells of the sliced ​​tissue according to the three-dimensional spatial model; Determining a cell identifier and a cell gene expression value of the slice sample according to the gene data; Determine the pseudo-space-time distance of cells of the slice sample using the virtual space algorithm according to the cell identifier and the cell gene expression value; The comprehensive spatial distance is calculated according to the cell physical distance and the cell pseudo-spatiotemporal distance. According to the comprehensive spatial distance, the cell spatial trajectory of the target single cell is determined.

6. The method for obtaining single cells with precise spatial localization from tissue sections as claimed in claim 5, characterized in that: The registering the image data based on the image features to obtain the registration data includes: A feature matching algorithm is defined for the image features, and based on the feature matching algorithm, original feature points and matching feature points of the image data are determined; constructing an image transformation model of the image data according to the original feature points; Determining the objective function of the image transformation model according to the original feature points and the matching feature points; Calculating optimal transformation parameters of the image transformation model according to the objective function; Registration data of the image data is determined according to the optimal transformation parameters.

7. The method for obtaining single cells with precise spatial localization from tissue sections as claimed in claim 1, characterized in that: The step of constructing a cutting path for the slice sample using a preset path planning algorithm according to the spatial positioning includes: Determining a cutting start point and a cutting end point of the slice sample according to the spatial positioning; Analyzing the cell structure and cell distribution status of the slice sample; Determining cutting constraints of the slice sample according to the cell structure and the cell distribution state; Analyzing the tissue properties of the slice sample, and determining the cutting parameters of the slice sample according to the tissue properties; According to the cutting constraint conditions and the cutting parameters, using the path planning algorithm, determining an initial cutting path from the cutting start point to the cutting end point; The feasibility of the initial cutting path is verified, and when the feasibility meets a preset feasibility threshold, the initial cutting path is used as the cutting path of the slice sample.

8. The method for obtaining single cells with precise spatial positioning from tissue sections as claimed in claim 1, characterized in that: Based on the cutting path, the sliced ​​sample is cut by using a preset laser cutter to obtain a cut sample, including: Precision calibrating the laser cutter to obtain a calibrated laser cutter; Determining the laser power, cutting speed and cutting depth of the calibration laser cutter according to the cutting path; analyzing a cutting path of the calibration laser cutter according to the laser power, the cutting speed, and the cutting depth; constructing a cutting path monitoring module for the calibration laser cutter according to the analyzed cutting path and the cutting path; Based on the cutting path monitoring module, the sliced ​​sample is cut to obtain a cut sample.

9. The method for obtaining single cells with precise spatial localization from tissue sections as claimed in claim 1, characterized in that: The step of constructing a pressure gradient environment for the cut sample comprises: Determining the microfluidic chip of the cut sample, and constructing the channel layout of the microfluidic chip; According to the channel layout, configuring a pressure controller of the microfluidic chip; Analyzing the separation requirements of the cut sample, and determining the pressure gradient parameters of the cut sample according to the separation requirements; A pressure gradient environment of the cut sample is constructed according to the pressure gradient parameter and the pressure controller.

10. A tissue slice acquisition system with precise spatial positioning of single cells, characterized in that: The system comprises: A tissue slicing module is used to obtain a target tissue sample of a target single cell, configure a fixative for the target tissue sample, fix the target tissue sample based on the fixative to obtain a fixed tissue sample, embed the fixed tissue sample with a preset resin to obtain an embedded tissue sample, and slice the embedded tissue sample to obtain a slice sample; A sample sequencing module is used to obtain the spatial transcriptome chip of the slice sample, label the target mRNA molecule of the slice sample using the corresponding probe of the spatial transcriptome chip to obtain the labeled slice sample, construct a sequencing library of the labeled slice sample, and sequence the labeled slice sample based on the sequencing library using a preset sequencing algorithm to obtain single-cell sequencing data; A cell positioning module is used to compare the single-cell sequencing data with the target gene corresponding to the target single cell, obtain the gene data of the barcode corresponding to the probe, collect the image data of the slice sample, and construct the cell space trajectory of the target single cell based on the image data and the gene data using a preset virtual space algorithm, and determine the spatial positioning of the target single cell according to the cell space trajectory; A laser cutting module, configured to construct a cutting path for the sliced ​​sample using a preset path planning algorithm according to the spatial positioning, and cut the sliced ​​sample using a preset laser cutter based on the cutting path to obtain a cut sample; The single cell acquisition module is used to construct a pressure gradient environment for the cut sample, and to separate the target single cell of the cut sample based on the pressure gradient environment.

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