Design method of high-efficiency marker probe for targeted early cartilage senescence detection

Abstract

The invention discloses a design method of an efficient marker probe for targeted early cartilage senescence detection. In the process of designing the marker probe for targeted early cartilage senescence detection, proteomics analysis is carried out on the protein of the early cartilage senescence tissue, the effect and related mechanism of the early cartilage senescence tissue are evaluated, a foundation is laid for comprehensively illuminating the pathophysiology mechanism of early cartilage senescence, and the method has a wide application prospect. All proteins in a biological sample can be comprehensively detected and analyzed, and a more comprehensive information basis is provided. Therefore, potential markers or biomarkers can be found easily, and more possibilities are provided for probe design. Protein related to a specific physiological or pathological state can be screened out by comparing proteomics data under different conditions, so that potential biomarkers for disease diagnosis, prediction and monitoring are found, and the detection accuracy is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of cartilage aging detection, and specifically is a method for designing a marker probe for efficient targeted early cartilage aging detection. Background Art

[0002] Cartilage aging testing refers to a series of methods to evaluate and monitor the health and aging of cartilage tissue. Cartilage is the connective tissue that connects bones. It plays a role in shock absorption, cushioning and protecting the joint surface in the joint. The aging and degeneration of cartilage can cause joint pain, stiffness and dysfunction, which in turn affects the quality of life.

[0003] However, the common early cartilage aging detection process has a relatively low detection efficiency, which makes the subsequent test results inaccurate, which may affect the progress of the overall experiment. Summary of the invention

[0004] The purpose of the present invention is to provide an efficient method for designing marker probes for detecting early cartilage aging in order to solve the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows: a highly efficient method for designing a marker probe for detecting early cartilage aging, the method comprising the following steps:

[0006] S1: First, perform bioinformatics analysis: Use bioinformatics tools to analyze the gene expression profile in chondrocytes and screen candidate genes or proteins related to cartilage aging. These genes or proteins may play an important role in early cartilage aging;

[0007] S2: Construct a targeted early cartilage aging database to obtain species and corresponding reference genome record information;

[0008] S3: Construct a cartilage aging target database to obtain a reference genome set for conservation analysis and perform gene annotation;

[0009] S4: Proteomic analysis: Use proteomics to identify proteins with significant changes in abundance in cartilage tissue and screen out markers related to cartilage aging

[0010] S5: Analyze and select conservative regions, then analyze specific regions and generate conservative specific regions; conduct in-depth research on key signaling pathways involved in chondrocyte biological processes, identify key regulatory factors and targets in the early cartilage aging process, and then generate candidate probe sets and annotate the candidate probes.

[0011] S6: Using molecular simulation technology, design targeted drugs or probes for specific markers to achieve efficient detection and intervention of early cartilage aging, and filter the candidate probes based on capture performance; then analyze the conservation and specificity of the probes; output single-species synthetic probes, and then the entire efficient targeted early cartilage aging detection marker probe design process can be completed.

[0012] In a preferred embodiment, in step S2, constructing a database targeting early cartilage aging tissue includes: generating species and corresponding reference genome record information based on a whole genome reference genome; the download source of the whole genome reference genome includes the NCBI genome library.

[0013] In a preferred embodiment, in step S3, the cartilage aging target database includes: incorporating all species names to be designed according to the taxonomic level of the target in the NCBI taxonomy library, searching all reference cartilage aging genomes according to the species name, forming a reference cartilage aging genome set for conservation analysis, and downloading the cartilage aging gene annotation file corresponding to the genome.

[0014] In a preferred embodiment, in step S4, an appropriate amount of cartilage tissue is weighed, protein lysis buffer, protease inhibitors and phosphatase inhibitors are added, and the sample is fully ground in a tissue grinder. The protein concentration is measured by BCA method, and the expression level of aging protein in the cartilage tissue is analyzed after electrophoresis, transfer, blocking and development.

[0015] In a preferred embodiment, in step S4, the protein is extracted by SDT cleavage method, protein is quantified by BCA method, and then the sample is digested by trypsin by FASP enzymatic method. Each sample is separated by HPLC liquid phase system Easy nLC with nanoliter flow rate. After chromatographic separation, the sample is analyzed by mass spectrometry using timsToF Pro mass spectrometer.

[0016] In a preferred embodiment, in step S4, the subcellular structure prediction software CELLO is used to perform subcellular localization analysis on the differential proteins, the Blast2Go software is used to perform gene ontology function annotation on the differential proteins, the differential proteins are annotated through the Kyoto Encyclopedia of Genes and Genomes (KEGG), and the protein-protein interaction (PPI) network is drawn by using CytoScape software.

[0017] In a preferred embodiment, in step S4, statistical processing is required in the process of identifying proteins with significant abundance changes in cartilage tissue, using GraphPad Prism9.0 software and R software. The two groups were compared using the Student's t test, and the IPGTT and IT experiments used repeated measures analysis of variance. Proteomics uses the difference fold (FC) upregulation> 1.5 times or downregulation< 0.67 times, P<0.05 as the standard to screen differential proteins, and the significance level of proteins in GO analysis or KEGG pathways is evaluated by Fisher's exact test, and P<0.05 is statistically significant.

[0018] In a preferred embodiment, in step S5, the criterion for selecting cartilage aging conserved regions is: a sequence set covering > 80% of the cartilage aging genome, and generating conserved cartilage aging specific regions includes: tracing the obtained specific conserved sequence set back to the position of the cartilage aging genome, outputting a specific conserved bed file, and filtering regions < 200bp.

[0019] In a preferred embodiment, in step S6, when designing multi-species and multi-level probes targeting early cartilage tissue, probe clustering is further performed to select representative probes as a synthetic probe set;

[0020] The method for selecting representative probes includes: using a sequence similarity clustering algorithm according to 90%-98% clustering, and selecting representative probes in each cartilage aging tissue cluster as a synthetic probe set.

[0021] In a preferred embodiment, in step S6, the effectiveness and specificity of the designed marker probe are verified by in vitro cell lines and animal models, and its potential for application in early cartilage aging detection is further verified.

[0022] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0023] In the present invention, in the process of designing a marker probe for detecting targeted early cartilage aging, the proteins of early cartilage aging tissue were analyzed by proteomics, and the role and related mechanisms of early cartilage aging tissue were evaluated, which laid the foundation for comprehensively clarifying the pathophysiological mechanism of early cartilage aging. All proteins in biological samples can be fully detected and analyzed, providing a more comprehensive information basis. This helps to discover potential markers or biomarkers and provides more possibilities for probe design; by comparing proteomics data under different conditions, proteins related to specific physiological or pathological states can be screened out, thereby discovering potential biomarkers for disease diagnosis, prediction and monitoring. Proteomics analysis can provide quantitative information on proteins, including the expression level and change trend of proteins under different conditions, which helps to understand the dynamic changes of biological systems and provide a more accurate basis for probe design. Proteomics technology has the characteristics of high sensitivity and high throughput, can detect a large number of proteins at the same time, and analyze complex biological samples quickly and efficiently, accelerating the discovery of biomarkers and the process of probe design. Through proteomics analysis, accurate detection of individual biomarkers and formulation of personalized treatment plans can be achieved, providing personalized directions and strategies for probe design. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. 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.

[0025] Example:

[0026] A highly efficient method for designing a marker probe for detecting early cartilage aging, the method comprising the following steps:

[0027] S1: First, perform bioinformatics analysis: Use bioinformatics tools to analyze the gene expression profile in chondrocytes and screen candidate genes or proteins related to cartilage aging. These genes or proteins may play an important role in early cartilage aging;

[0028] S2: Construct a targeted early cartilage aging database to obtain species and corresponding reference genome record information;

[0029] S3: Construct a cartilage aging target database to obtain a reference genome set for conservation analysis and perform gene annotation;

[0030] S4: Proteomic analysis: Use proteomics to identify proteins with significant changes in abundance in cartilage tissue and screen out markers related to cartilage aging

[0031] S5: Analyze and select conservative regions, then analyze specific regions and generate conservative specific regions; conduct in-depth research on key signaling pathways involved in chondrocyte biological processes, identify key regulatory factors and targets in the early cartilage aging process, and then generate candidate probe sets and annotate the candidate probes.

[0032] S6: Using molecular simulation technology, design targeted drugs or probes for specific markers to achieve efficient detection and intervention of early cartilage aging, and filter the candidate probes based on capture performance; then analyze the conservation and specificity of the probes; output single-species synthetic probes, and then the entire efficient targeted early cartilage aging detection marker probe design process can be completed.

[0033] 2. An efficient method for designing marker probes for detecting early cartilage aging as described in claim 1, characterized in that: in the step S2, constructing a database targeting early cartilage aging tissues includes: generating species and corresponding reference genome record information based on the whole genome reference genome; the download source of the whole genome reference genome includes the NCBI genome library.

[0034] In step S3, the cartilage aging target database includes: incorporating all species names to be designed according to the taxonomic level of the target in the NCBI taxonomy library, searching all reference cartilage aging genomes according to the species name, forming a reference cartilage aging genome set for conservation analysis, and downloading the cartilage aging gene annotation file corresponding to the genome.

[0035] In step S4, an appropriate amount of cartilage tissue is weighed, protein lysis buffer, protease inhibitors and phosphatase inhibitors are added, and the sample is fully ground in a tissue grinder. The protein concentration is measured by BCA method, and the expression level of aging protein in the cartilage tissue is analyzed after electrophoresis, transfer, blocking and development.

[0036] In step S4, the protein was extracted by SDT cleavage method, protein was quantified by BCA method, and then the sample was digested by trypsin by FASP enzymatic method. Each sample was separated by HPLC liquid phase system Easy nLC with nanoliter flow rate. After chromatographic separation, the sample was analyzed by mass spectrometry using timsToF Pro mass spectrometer.

[0037] In step S4, the subcellular structure prediction software CELLO is used to perform subcellular localization analysis on the differential proteins, the Blast2Go software is used to perform gene ontology function annotation on the differential proteins, the differential proteins are annotated through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the protein-protein interaction (PPI) network is drawn by using CytoScape software.

[0038] In step S4, statistical processing is required in the process of identifying proteins with significant abundance changes in cartilage tissue, using GraphPad Prism 9.0 software and R software. The two groups were compared using the Student's t test, and the IPGTT and IT experiments used repeated measures analysis of variance. Proteomics used the difference fold (FC) upregulation > 1.5 times or downregulation < 0.67 times, P < 0.05 as the standard for screening differential proteins, and the significance level of proteins in GO analysis or KEGG pathways was evaluated by Fisher's exact test, and P < 0.05 was considered statistically significant.

[0039] In step S5, the standard for selecting cartilage aging conservative regions is: a sequence set covering >80% of the cartilage aging genome, and generating conservative cartilage aging specific regions includes: tracing the obtained specific conservative sequence set back to the position of the cartilage aging genome, outputting a specific conservative bed file, and filtering the region <200bp.

[0040] In the step S6, when designing multi-species and multi-level probes targeting early cartilage tissue, probe clustering is further performed to select representative probes as a synthetic probe set;

[0041] The method for selecting representative probes includes: using a sequence similarity clustering algorithm according to 90%-98% clustering, and selecting representative probes in each cartilage aging tissue cluster as a synthetic probe set.

[0042] In step S6, the effectiveness and specificity of the designed marker probe are verified by in vitro cell lines and animal models, and its potential for application in early cartilage aging detection is further verified.

[0043] In the present invention, in the process of designing a marker probe for detecting targeted early cartilage aging, the proteins of early cartilage aging tissue were analyzed by proteomics, and the role and related mechanisms of early cartilage aging tissue were evaluated, which laid the foundation for comprehensively clarifying the pathophysiological mechanism of early cartilage aging. All proteins in biological samples can be fully detected and analyzed, providing a more comprehensive information basis. This helps to discover potential markers or biomarkers and provides more possibilities for probe design; by comparing proteomics data under different conditions, proteins related to specific physiological or pathological states can be screened out, thereby discovering potential biomarkers for disease diagnosis, prediction and monitoring. Proteomics analysis can provide quantitative information on proteins, including the expression level and change trend of proteins under different conditions, which helps to understand the dynamic changes of biological systems and provide a more accurate basis for probe design. Proteomics technology has the characteristics of high sensitivity and high throughput, can detect a large number of proteins at the same time, and analyze complex biological samples quickly and efficiently, accelerating the discovery of biomarkers and the process of probe design. Through proteomics analysis, accurate detection of individual biomarkers and formulation of personalized treatment plans can be achieved, providing personalized directions and strategies for probe design.

[0044] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or still includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0045] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An efficient method for designing a marker probe for detecting early cartilage aging, characterized in that: The method comprises the following steps: S1: Bioinformatics analysis is performed first: the gene expression profile in chondrocytes is analyzed by bioinformatics tools to screen candidate genes or proteins related to cartilage aging; these genes or proteins may play an important role in early cartilage aging; S2: Construct a targeted early cartilage aging database to obtain species and corresponding reference genome record information; S3: Construct a cartilage aging target database to obtain a reference genome set for conservation analysis and perform gene annotation; S4: Proteomic analysis: Use proteomics to identify proteins with significant changes in abundance in cartilage tissue and screen out markers related to cartilage aging S5: Analyze and select conservative regions, then analyze specific regions and generate conservative specific regions; conduct in-depth research on key signaling pathways involved in chondrocyte biological processes, identify key regulatory factors and targets in the early cartilage aging process, and then generate candidate probe sets and annotate the candidate probes. S6: Using molecular simulation technology, design targeted drugs or probes for specific markers to achieve efficient detection and intervention of early cartilage aging, and filter the candidate probes based on capture performance; then analyze the conservation and specificity of the probes; output single-species synthetic probes, and then the entire efficient targeted early cartilage aging detection marker probe design process can be completed.

2. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In the step S2, constructing a database targeting early cartilage aging tissues includes: generating species and corresponding reference genome record information according to the whole genome reference genome; the download source of the whole genome reference genome includes the NCBI genome library.

3. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S3, the cartilage aging target database includes: incorporating all species names to be designed according to the taxonomic level of the target in the NCBI taxonomy library, searching all reference cartilage aging genomes according to the species name, forming a reference cartilage aging genome set for conservation analysis, and downloading the cartilage aging gene annotation file corresponding to the genome.

4. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S4, an appropriate amount of cartilage tissue is weighed, protein lysis buffer, protease inhibitors and phosphatase inhibitors are added, and the sample is fully ground in a tissue grinder. The protein concentration is measured by BCA method, and the expression level of aging protein in the cartilage tissue is analyzed after electrophoresis, transfer, blocking and development.

5. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S4, the protein is extracted by SDT lysis method, the protein is quantified by BCA method, and then the sample is digested by trypsin by FASP enzymatic method; Each sample was separated using the HPLC liquid phase system Easy nLC with a nanoliter flow rate; after chromatographic separation, the samples were analyzed by mass spectrometry using a timsToF Pro mass spectrometer.

6. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S4, the subcellular structure prediction software CELLO is used to perform subcellular localization analysis on the differential proteins, the Blast2Go software is used to perform gene ontology function annotation on the differential proteins, the differential proteins are annotated through the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the protein-protein interaction (PPI) network is drawn by using CytoScape software.

7. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S4, statistical processing is required in the process of identifying proteins with significant abundance changes in cartilage tissue, using GraphPad Prism 9.0 software and R software; the two groups are compared using the Student's t-test, and the IPGTT and IT experiments use repeated measures analysis of variance; proteomics uses the difference fold (FC) upregulation>1.5 times or downregulation<0.67 times, P<0.05 as the standard to screen differential proteins, and the significance level of proteins in GO analysis or KEGG pathways is evaluated by Fisher's exact test, and P<0.05 indicates that the difference is statistically significant.

8. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S5, the standard for selecting cartilage aging conservative regions is: a sequence set covering >80% of the cartilage aging genome, and generating conservative cartilage aging specific regions includes: tracing the obtained specific conservative sequence set back to the position of the cartilage aging genome, outputting a specific conservative bed file, and filtering the region <200bp.

9. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S6, when designing multi-species and multi-level probes targeting early cartilage tissue, probe clustering is further performed to select representative probes as a synthetic probe set. The method for selecting representative probes includes: using a sequence similarity clustering algorithm according to 90%-98% clustering, and selecting representative probes in each cartilage aging tissue cluster as a synthetic probe set.

10. The method for designing an efficient marker probe for detecting early cartilage aging as claimed in claim 1, characterized in that: In step S6, the effectiveness and specificity of the designed marker probe are verified by in vitro cell lines and animal models, and its potential for application in early cartilage aging detection is further verified.