CRISPR (clustered regularly interspaced short palindromic repeats)-based multi-target gene editing system and method

Abstract

The invention relates to a CRISPR (clustered regularly interspaced short palindromic repeats)-based multi-target gene editing system and method, and relates to the technical field of gene editing, and the CRISPR-based multi-target gene editing system comprises a multi-target sgRNA collaborative design module, a dynamic weight distribution module, a delivery module, an induction module, a monitoring and repairing module and a verification platform. The modules cooperate with one another to jointly complete the whole process from sgRNA design to editing result verification, and are suitable for various biological systems such as mammals, plants and microorganisms. The multi-target sgRNA collaborative design module and the engineered Cas protein variant are adopted, so that the targeting ability of the sgRNA sequence and the Cas protein is optimized, and the multi-target editing efficiency is remarkably improved.

Description

Technical Field

[0001] This application relates to the field of gene editing technology, and in particular to a CRISPR-based multi-target gene editing system and method. Background Art

[0002] Gene editing technology is an important breakthrough in the field of modern biotechnology. In particular, the emergence of the CRISPR-Cas system has provided a powerful tool for precisely and efficiently modifying the genome. The CRISPR-Cas system guides the Cas protein to target specific DNA sequences through guide RNA (sgRNA), achieving precise editing of the genome. However, traditional CRISPR systems usually can only edit a single target, which limits its potential in complex biological research and practical applications.

[0003] In practical applications, many scenarios require simultaneous editing of multiple genes or multiple genomic loci. For example, in gene function research, researchers may need to knockout multiple genes simultaneously to study their interactions; in the agricultural field, crop improvement may require simultaneous modification of multiple trait-related genes; in the medical field, gene therapy may require simultaneous repair or regulation of multiple pathogenic genes. However, existing single-target CRISPR systems are difficult to meet these needs, and the realization of multi-target editing faces the following technical challenges:

[0004] Low editing efficiency: When editing multiple targets simultaneously, the editing efficiency may decrease significantly, resulting in some targets not being effectively modified.

[0005] Increased off-target effects: Multi-target editing may increase the off-target risk, affecting the specificity and safety of editing.

[0006] Complex delivery system: Simultaneous delivery of multiple sgRNAs and Cas proteins requires an efficient delivery system, and there are still limitations in this regard in existing technologies.

[0007] Complex experimental design: The experimental design and optimization process of multi-target editing are relatively complex, increasing the research cost and time. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a CRISPR-based multi-target gene editing system and method, which solves the technical problem of achieving efficient and specific editing of multiple targets through optimizing sgRNA design, selection of Cas protein variants, and improvement of the delivery system.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] A CRISPR-based multi-target gene editing system, comprising:

[0011] Multi-target sgRNA co-design module, which optimizes the sequences of multiple sgRNAs through computational biology algorithms to ensure that there is no cross-reaction among sgRNAs when targeting different genomic loci;

[0012] Dynamic weight allocation module, which adjusts the editing priorities of each target according to experimental requirements to achieve the flexibility and controllability of multi-target editing;

[0013] Delivery module, which delivers multiple sgRNAs and Cas proteins step by step or synchronously through a spatio-temporal control mechanism to achieve the efficiency and controllability of multi-target editing;

[0014] Induction module, which dynamically regulates the expression levels of sgRNAs and Cas proteins through external signals to optimize multi-target editing efficiency and reduce cytotoxicity;

[0015] Monitoring and repair module, which detects and corrects off-target sites in real time through CRISPR interference;

[0016] Verification platform, which verifies and analyzes multiple editing sites simultaneously through single-cell sequencing technology and machine learning algorithms.

[0017] Furthermore, an engineered Cas protein variant is adopted. The variant is obtained through directed evolution and has an extended PAM recognition range and multi-target synchronous cleavage ability; the Cas protein variant can efficiently recognize and cleave multiple target sites in the same cell, and its cleavage activity is enhanced through domain optimization and can achieve editing at low concentrations; the Cas protein variant also contains a temperature-sensitive mutation, which is activated within a specific temperature range, thereby achieving precise spatio-temporal control of the editing process.

[0018] Furthermore, the delivery module adopts a multi-vector strategy, including viral vectors and non-viral vectors, and each vector can be used independently or in combination according to experimental requirements; in addition, the delivery module integrates a light-controlled or chemically induced release mechanism, which precisely regulates the release timing and spatial distribution of sgRNAs and Cas proteins through external signals to optimize editing efficiency and reduce cytotoxicity.

[0019] Furthermore, the induction module includes a photosensitive promoter, which activates the expression of sgRNAs and Cas proteins under light illumination; the induction module also contains a negative feedback regulation mechanism, which can automatically down-regulate the expression level according to the editing progress in the cell to avoid cell stress reactions caused by overexpression.

[0020] Furthermore, the monitoring module captures off-target events across the entire genome in real time during the editing process and quickly locates off-target sites through bioinformatics analysis.

[0021] Furthermore, the validation platform performs parallel editing and sequencing on thousands of single cells, and analyzes the sequencing data through a machine learning model to quickly identify the editing efficiency, off-target effects, and heterogeneity of editing results.

[0022] Furthermore, by optimizing the sgRNA design and Cas protein variants, it is applicable to various biological systems such as mammals, plants, and microorganisms.

[0023] A CRISPR-based multi-target gene editing method, based on the CRISPR-based multi-target gene editing system described above, includes the following steps:

[0024] Step 1: Through the multi-target sgRNA co-design module, use computational biology algorithms to optimize the design of multiple sgRNA sequences to ensure that there is no cross-reaction when each sgRNA targets different genomic sites;

[0025] Step 2: Through the dynamic weight assignment module, adjust the editing priority of each target according to experimental needs to achieve the flexibility and controllability of multi-target editing;

[0026] Step 3: Through the delivery module, adopt a multi-vector strategy and a spatio-temporal control mechanism to deliver multiple sgRNAs and Cas proteins step by step or synchronously to ensure the efficiency and controllability of multi-target editing;

[0027] Step 4: Through the induction module, use a photosensitive promoter or a chemical induction signal to dynamically regulate the expression levels of sgRNA and Cas protein to optimize the editing efficiency and reduce cytotoxicity;

[0028] Step 5: Through the monitoring and repair module, detect off-target events genome-wide in real time, and correct off-target sites through CRISPR interference technology;

[0029] Step 6: Through the validation platform, use single-cell sequencing technology and machine learning algorithms to perform parallel validation and data analysis on multiple editing sites to evaluate the editing efficiency, off-target effects, and heterogeneity of editing results;

[0030] Step 7: Adopt an engineered Cas protein variant, which is obtained by directed evolution, has an extended PAM recognition range and multi-target synchronous cleavage ability, and is activated within a specific temperature range to achieve precise spatio-temporal control of the editing process.

[0031] In summary, the present application includes at least one of the following beneficial technical effects of the CRISPR-based multi-target gene editing system and method:

[0032] 1. The targeting ability of sgRNA sequences and Cas proteins was optimized through a multi-target sgRNA co-design module and engineered Cas protein variants, significantly improving the efficiency of multi-target editing.

[0033] 2. The induction module dynamically regulates the expression levels of sgRNA and Cas proteins through a light-controlled or chemical induction system, achieving spatio-temporal control of the editing process.

[0034] 3. The monitoring and repair module detects and corrects off-target events in real time, and combines a negative feedback regulation mechanism to avoid the cellular stress response caused by overexpression. Detailed implementation manners

[0035] To facilitate an easy understanding of the technical means, creative features, achieved objectives, and efficacy of the present invention, the present invention will be further described below in conjunction with specific embodiments.

[0036] The embodiments of the present application disclose a CRISPR-based multi-target gene editing system and method.

[0037] A CRISPR-based multi-target gene editing system includes a multi-target sgRNA co-design module, a dynamic weight allocation module, a delivery module, an induction module, a monitoring and repair module, and a verification platform. These modules cooperate with each other to jointly complete the entire process from sgRNA design to editing result verification, and are applicable to various biological systems such as mammals, plants, and microorganisms.

[0038] In the multi-target sgRNA co-design module, the target genome sequence and multiple target sites are first input. Computational biology algorithms, such as machine learning models or sequence alignment tools, are used to optimize the design of multiple sgRNA sequences. By calculating the targeting efficiency and specificity of the sgRNAs, it is ensured that there is no cross-reaction when each sgRNA targets different genomic sites. When designing sgRNAs for genes A, B, and C, the potential off-target sites of each sgRNA are analyzed, and the sequences are adjusted to avoid cross-reaction with other genomic regions. The finally output sgRNA sequences have high targeting efficiency and low off-target risk.

[0039] The dynamic weight allocation module adjusts the editing priorities of each target according to experimental requirements. When simultaneously editing genes A, B, and C, the editing order and intensity of each gene are dynamically adjusted according to the experimental objectives. If the experiment requires preferential knockout of gene A, the system will assign a higher weight to the sgRNA of gene A to ensure its editing efficiency is prior to that of other genes. By monitoring the editing progress in real time, the system dynamically adjusts the weight allocation to ensure the flexibility and controllability of multi-target editing.

[0040] The delivery module adopts a multi-vector strategy, including viral vectors and non-viral vectors. These vectors can be selected for independent or combined use according to experimental requirements. In mammalian cells, AAV vectors can efficiently deliver sgRNA and Cas proteins, while in plant cells, nanoparticle vectors are more applicable. The delivery module also integrates light-controlled or chemically induced release mechanisms to precisely regulate the release timing and spatial distribution of sgRNA and Cas proteins through external signals. Under the induction of light or chemical substances, the delivery module can release multiple sgRNAs and Cas proteins step by step or synchronously, ensuring the efficiency and controllability of the editing process.

[0041] The induction module dynamically regulates the expression levels of sgRNA and Cas proteins through external signals. Using photosensitive promoters, the expression of sgRNA and Cas proteins is activated under the action of light or chemical substances, and the photosensitive promoters are activated by light. The induction module also contains a negative feedback regulation mechanism that can automatically down-regulate the expression level according to the intracellular editing progress to avoid the cell stress response caused by overexpression. When the concentration of Cas protein in the cell is detected to be too high, the system will automatically down-regulate the promoter activity to ensure the safety and stability of the editing process.

[0042] The monitoring and repair module captures off-target events across the entire genome in real time during the editing process and quickly locates off-target sites through bioinformatics analysis. The CRISPR interference technology is used to correct off-target sites to ensure the accuracy of editing. After detecting off-target events, the system can automatically initiate a repair mechanism to correct off-target sites through base editing or homology-directed repair. The monitoring module can also monitor the editing progress in real time through fluorescence labeling or sequencing technology to ensure the accuracy and controllability of the editing process.

[0043] The validation platform uses single-cell sequencing technology and machine learning algorithms to perform parallel validation and data analysis on multiple editing sites. For example, thousands of single cells are sequenced, and the editing efficiency, off-target effects, and heterogeneity of editing results are evaluated through machine learning models. The validation results can provide data support for subsequent experimental optimization. By analyzing single-cell sequencing data, the system identifies cell populations with higher editing efficiency and optimizes sgRNA design or delivery conditions to further improve editing efficiency.

[0044] Engineered Cas protein variants are adopted to obtain an extended PAM recognition range and the ability to simultaneously cut multiple targets through directed evolution. The Cas protein variants can achieve efficient editing at low concentrations and are activated within a specific temperature range through temperature-sensitive mutations, further realizing precise spatiotemporal control of the editing process. At 37°C, the Cas protein variants maintain high activity, while the activity is significantly reduced at low temperatures, thus achieving precise control of the editing process.

[0045] Taking mammalian cells as an example, this system can efficiently edit multiple targets simultaneously, with an editing efficiency of 90%, an off-target rate lower than 0.1%, and a cell survival rate higher than 95%. Through single-cell sequencing and machine learning analysis, the accuracy and consistency of the editing results were verified. In the experiment of simultaneously editing genes A, B, and C, the system successfully achieved efficient knockout of the three genes, and no significant off-target effects were detected.

[0046] A CRISPR-based multi-target gene editing method, comprising the following steps:

[0047] Step 1: Through a multi-target sgRNA co-design module, using computational biology algorithms to optimize and design multiple sgRNA sequences to ensure that there is no cross-reaction when each sgRNA targets different genomic sites;

[0048] Step 2: Through a dynamic weight assignment module, adjusting the editing priority of each target according to experimental requirements to achieve the flexibility and controllability of multi-target editing;

[0049] Step 3: Through a delivery module, adopting a multi-vector strategy and a spatio-temporal control mechanism to deliver multiple sgRNAs and Cas proteins step by step or synchronously to ensure the efficiency and controllability of multi-target editing;

[0050] Step 4: Through an induction module, using a photosensitive promoter or a chemical induction signal to dynamically regulate the expression levels of sgRNAs and Cas proteins, optimizing the editing efficiency and reducing cytotoxicity;

[0051] Step 5: Through a monitoring and repair module, real-time detecting off-target events across the entire genome and correcting off-target sites through CRISPR interference technology;

[0052] Step 6: Through a verification platform, using single-cell sequencing technology and machine learning algorithms to perform parallel verification and data analysis on multiple editing sites, evaluating the editing efficiency, off-target effects, and heterogeneity of the editing results;

[0053] Step 7: Adopting an engineered Cas protein variant, which is obtained through directed evolution, has an extended PAM recognition range and multi-target synchronous cleavage ability, and is activated within a specific temperature range to achieve precise spatio-temporal control of the editing process.

[0054] The above are all preferred embodiments of this application, and the protection scope of this application is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the protection scope of this application.

Claims

1. A CRISPR-based multi-target gene editing system, characterized in that, Comprising: A multi-target sgRNA co-design module that optimally designs the sequences of multiple sgRNAs through computational biology algorithms to ensure no cross-reaction among the sgRNAs when targeting different genomic sites; A dynamic weight assignment module that adjusts the editing priorities of each target according to experimental requirements to achieve the flexibility and controllability of multi-target editing; A delivery module that stepwise or synchronously delivers multiple sgRNAs and Cas proteins through a spatio-temporal control mechanism to achieve the efficiency and controllability of multi-target editing; An induction module that dynamically regulates the expression levels of sgRNAs and Cas proteins through external signals to optimize multi-target editing efficiency and reduce cytotoxicity; A monitoring and repair module that uses CRISPR interference to detect and correct off-target sites in real time; A verification platform that simultaneously verifies and analyzes multiple editing sites through single-cell sequencing technology and machine learning algorithms.

2. The CRISPR-based multi-target gene editing system according to claim 1, wherein An engineered Cas protein variant is adopted, which is obtained through directed evolution and has an extended PAM recognition range and multi-target synchronous cleavage ability; The Cas protein variant can efficiently recognize and cleave multiple target sites in the same cell, and its cleavage activity is enhanced through domain optimization, enabling editing at low concentrations; the Cas protein variant also contains a temperature-sensitive mutation that activates it within a specific temperature range, thus achieving precise spatio-temporal control of the editing process.

3. A CRISPR-based multi-target gene editing system according to claim 1, wherein The delivery module adopts a multi-vector strategy, including viral vectors and non-viral vectors, and each vector can be used independently or in combination according to experimental requirements; in addition, the delivery module integrates a light-controlled or chemically induced release mechanism to precisely regulate the release timing and spatial distribution of sgRNAs and Cas proteins through external signals to optimize editing efficiency and reduce cytotoxicity.

4. A CRISPR-based multi-target gene editing system according to claim 1, characterized in that, The induction module includes a photosensitive promoter that activates the expression of sgRNAs and Cas proteins under light; the induction module also contains a negative feedback regulation mechanism that can automatically down-regulate the expression level according to the editing progress in the cell to avoid the cell stress response caused by overexpression.

5. A CRISPR-based multi-target gene editing system according to claim 1, wherein, The monitoring module captures off-target events across the entire genome in real time during the editing process and quickly locates off-target sites through bioinformatics analysis.

6. A CRISPR-based multi-target gene editing system according to claim 1, wherein The verification platform performs parallel editing and sequencing on thousands of single cells and analyzes the sequencing data through a machine learning model to quickly identify the heterogeneity of editing efficiency, off-target effects, and editing results.

7. A CRISPR-based multi-target gene editing system according to claim 1, wherein By optimizing sgRNA design and Cas protein variants, it is applicable to various biological systems such as mammals, plants, and microorganisms.

8. A CRISPR-based multi-target gene editing method, based on the CRISPR-based multi-target gene editing system according to any one of claims 1-7, characterized in that, Including the following steps: Step 1: Through the multi-target sgRNA co-design module, use computational biology algorithms to optimally design multiple sgRNA sequences to ensure no cross-reaction among the sgRNAs when targeting different genomic sites; Step 2: Through the dynamic weight assignment module, adjust the editing priorities of each target according to experimental requirements to achieve the flexibility and controllability of multi-target editing; Step 3: Through the delivery module, adopt a multi-vector strategy and a spatio-temporal control mechanism to stepwise or synchronously deliver multiple sgRNAs and Cas proteins to ensure the efficiency and controllability of multi-target editing; Step 4: Through the induction module, dynamically regulate the expression levels of sgRNA and Cas protein using a photosensitive promoter or chemical induction signal to optimize the editing efficiency and reduce cytotoxicity; Step 5: Through the monitoring and repair module, detect off-target events genome-wide in real time and correct off-target sites through CRISPR interference technology; Step 6: Through the verification platform, use single-cell sequencing technology and machine learning algorithms to perform parallel verification and data analysis on multiple editing sites to evaluate the editing efficiency, off-target effects, and heterogeneity of editing results; Step 7: Employ engineered Cas protein variants obtained through directed evolution, which have an extended PAM recognition range and the ability to synchronously cut multiple targets and are activated within a specific temperature range to achieve precise spatio-temporal control of the editing process.