Method for exploring disease-related aptamer based on single-round SELEX (systematic evolution of ligands by exponential enrichment)

Abstract

The invention relates to a method for exploring disease-related aptamers based on single-round SELEX (systematic evolution of ligands by exponential enrichment), which comprises the following steps of: carrying out independent single-round SELEX screening on multiple patients and control samples, and selecting aptamers which conform to disease development rules and have obvious enrichment difference by combining a high-throughput sequencing technology and an omics difference analysis method; the nucleic acid aptamer which is expected to be used for biomarker exploration, precise disease diagnosis and staging and targeted drug delivery is obtained by combining the combination difference verification of a large sample queue.

Description

Technical Field

[0001] This invention belongs to the field of biomedical engineering, and specifically relates to a method for discovering disease-related nucleic acid aptamers based on single-round SELEX. Background Technology

[0002] Nucleic acid aptamers are single-stranded DNA or RNA oligonucleotide molecules that can be obtained through screening using the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) technique. Aptamers bind to various targets, including cells, proteins, nucleic acids, lipids, and small molecules, through non-covalent intermolecular interactions such as hydrogen bonds, electrostatic interactions, and van der Waals forces, exhibiting performance comparable to antibodies. Furthermore, due to their high stability, ease of synthesis and modification, convenient storage and transportation, low immunogenicity, and the fact that their preparation does not require animal immunization, they are considered promising novel molecular recognition elements that could replace antibodies, attracting significant attention in diagnostics, detection, treatment, and basic research.

[0003] Proteins are the main carriers of life activities and are closely related to the body's life processes and the occurrence and development of diseases. For biomarkers of major diseases, screening nucleic acid aptamers with excellent affinity and specificity for use as diagnostic probes, targeted drug leads, and functional blockers is an effective way to achieve early diagnosis, screening, and targeted therapy. However, nucleic acid aptamers obtained through classic SELEX technology often fail to meet these application requirements. This is because classic methods use proteins synthesized in eukaryotic or prokaryotic expression systems for screening, and differences in protein folding and modification can lead to a loss of affinity in the resulting nucleic acid aptamers. Furthermore, the mismatch between the buffer system used for screening and the complex in vivo environment can prevent nucleic acid aptamers from forming their preferred binding conformation, resulting in a significant decrease in affinity and specificity. Although SELEX technology based on complex targets such as cells, plasma, and tissues has been developed, the increased complexity and decreased abundance of targets affect the enrichment of preferred binding sequences, and commonly used affinity detection methods are difficult to achieve traversal, easily leading to the loss of nucleic acid aptamers. Therefore, it is necessary to innovate the traditional SELEX technology to enable the batch acquisition of nucleic acid aptamers for biomarkers of major diseases using complex targets. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a method for discovering disease-related nucleic acid aptamers based on single-round SELEX. The method aims to use multiple patient and control samples to perform independent single-round SELEX screening, and combine high-throughput sequencing technology and omics differential analysis methods to select nucleic acid aptamers that conform to the disease development pattern and have significant enrichment differences. Combined with the binding difference verification of a large sample cohort, nucleic acid aptamers that are expected to be used for biomarker discovery, precise disease diagnosis and staging, and targeted drug delivery are obtained.

[0005] This invention provides a method for discovering disease-related nucleic acid aptamers based on a single-round SELEX, comprising the following steps: S101. Couple the proteins in each patient and control biological sample to the surface of a solid matrix; S102. Obtain a set of nucleic acid aptamers that bind to the above proteins based on a single round of SELEX; S103. Through high-throughput sequencing and omics differential analysis, combined with biological principles, candidate nucleic acid aptamers with significant enrichment differences are retained; S104. Obtain the large sample queue; S105. Identify the nucleic acid aptamers that can distinguish between patient and control samples through binding difference verification using a large sample cohort.

[0006] Preferably, the patient and control biological samples in step S101 include one or more of whole blood, plasma, serum, urine, cells, and tissue sections.

[0007] Preferably, the solid matrix in step S101 includes one or more of magnetic beads, well plates, and gels that are bound to proteins through covalent and / or non-covalent interactions.

[0008] More preferably, the solid-phase matrix coupling method includes enriching low-abundance proteins in the sample using affinity magnetic beads or based on NanoPro. TM The 1000 protein analyzer uses the difference in isoelectric point to couple complex protein regions into capillary sections.

[0009] Preferably, the single-round SELEX method in step S102 includes the following steps: A random library of single-stranded DNA or RNA is incubated with proteins on the surface of a solid matrix in a liquid environment to allow the two to fully bind and form a protein-nucleic acid aptamer complex. Collect protein-nucleic acid aptamer complexes; The protein-nucleic acid aptamer complex is dissociated, and the aptamers are collected.

[0010] Preferably, in step S103, the high-throughput sequencing evaluates whether the sequencing data meets the analysis requirements based on the amount of data obtained from the sequencing, the error rate, and the percentage of valid data. For each sample, the sequencing results of the nucleic acid aptamer set obtained from the sequencing results must have at least 1 G of data obtained from the sequencing, Q20% > 90%, Q30% > 80%, and the percentage of valid data > 70%, which means that the requirements are met.

[0011] Preferably, the omics differential analysis in step S103 includes the following steps: Data homogenization and summarization: The data is homogenized using the total number of valid reads and the concentration of the nucleic acid aptamer set; sequences with initial reads < 5 are removed from each sequencing library, and the remaining sequences are intersected to complete the summarization; Overall parallelism and difference analysis: The repeatability of parallel groups was evaluated using the average CV value. Three parallel groups were set up for each biological sample. An average CV < 20% indicates good repeatability. Pearson correlation coefficient was used to evaluate intra-group parallelism. R > 0.8 and p < 0.05 indicates strong positive correlation within groups; R between 0.3 and 0.8 and p < 0.05 indicates positive correlation between groups; R < 0.3 or p ≥ 0.05 indicates no correlation. Principal component analysis was used to evaluate inter-group differences. The distribution of each experimental group in different regions indicates significant overall differences between groups. Differential analysis: The edgeR method was used to perform differential analysis on the sequencing data of nucleic acid aptamer sets obtained from patient and control samples, specifying |log2 FC Sequences with |>1 and p<0.05 are candidate nucleic acid aptamers, showing significant differences in binding amounts with patient and control samples.

[0012] Preferably, the binding difference verification in step S105 includes the following steps: (1) After equal amounts of the same biological samples were subjected to the same pretreatment, each sample was fully combined with an equal amount of nucleic acid aptamer in a liquid environment to obtain a “protein-nucleic acid aptamer” complex, and the complex was collected. (2) The protein-nucleic acid aptamer complex is fully dissociated, the nucleic acid aptamer is collected, and absolute quantitative detection is performed. The detection value is taken as the binding amount of the nucleic acid aptamer to the sample. (3) Compare whether there is a significant difference in the binding amount of the nucleic acid aptamer to the patient and control samples; if there is a significant difference and the difference factor is not less than 2, the nucleic acid aptamer is considered to be usable as a probe.

[0013] Preferably, the absolute quantitative detection in step (2) includes real-time quantitative PCR or digital PCR.

[0014] Beneficial effects (1) This invention uses multiple patient and control samples to conduct independent single-round SELEX screening, and combines high-throughput sequencing technology and omics differential analysis methods to select nucleic acid aptamers that conform to the disease development pattern and have significant enrichment differences. Combined with the binding difference verification of a large sample cohort, nucleic acid aptamers that are expected to be used for biomarker discovery, precise disease diagnosis and staging and targeted drug delivery are obtained.

[0015] (2) The two solid-phase coupling methods for complex proteins provided by this invention are: one is to use affinity magnetic beads to efficiently enrich low-abundance proteins in a sample; the other is to use a NanoPro™ 1000 protein analyzer to couple proteins in a sample into capillaries according to their isoelectric point differences. The above methods can be used in the single-round SELEX process described in this invention.

[0016] (3) Nucleic acid aptamers obtained by the method described in this invention can be used to fish for disease biomarkers, assist in biomarker analysis, pathogenic mechanism research, drug target determination, etc.; they can also be used as detection probes for early diagnosis and screening of diseases, accurate staging, etc.; or as drug lead for targeted therapy of diseases. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the present invention.

[0018] Figure 2 This is a flowchart illustrating the process of serum screening and enrichment for customized libraries.

[0019] Figure 3 These are the quality control results of serum screening and enrichment of customized libraries; where (A) is the recovery rate of each round, and (B) is the change in affinity between the enriched libraries and serum in each round.

[0020] Figure 4 This is a flowchart illustrating the process of discovering nucleic acid aptamer probes based on a single round of Mag-SELEX.

[0021] Figure 5 This is a schematic diagram of the process for discovering nucleic acid aptamer probes based on a single-round nanopro-SELEX.

[0022] Figure 6 These are the quality control results before the nucleic acid aptamer assembly library construction and sequencing; among them, (A) is based on a single round of Mag-SELEX, and (B) is based on a single round of nanopro-SELEX.

[0023] Figure 7 The results are shown in the principal component analysis diagram; (A) is based on a single-round Mag-SELEX, and (B) is based on a single-round nanopro-SELEX.

[0024] Figure 8 The bar chart shows the number of nucleic acid aptamers with significant fold differences obtained from the intergroup difference analysis; where (A) is based on a single round of Mag-SELEX and (B) is based on a single round of nanopro-SELEX.

[0025] Figure 9 The graph shows the results of the binding difference verification of a large sample cohort; where (A) to (D) are the binding amounts of MB_04, MB_30, N_11, and N_56 with each group of samples, respectively. Detailed Implementation

[0026] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0027] Unless otherwise stated, the buffers used in the examples are all DPBS buffers, with the following composition: 0.9 mM CaCl2, 2.7 mM KCl, 1.5 mM KH2PO4, 0.6 mM MgCl2·H2O, 0.1 M NaCl and 20 mM Na2HPO4, pH=7.4.

[0028] Figure 1 A flowchart illustrating a method for discovering disease-related nucleic acid aptamers based on a single-round SELEX algorithm provided by this invention includes steps S101 to S105: S101. Couple the proteins in each patient and control biological sample to the surface of a solid matrix; Patient and control biological samples, including but not limited to whole blood, plasma, serum, urine, cells, and tissue sections, are clinically detectable biological samples. To minimize differences in protein content caused by other confounding factors, patient and control biological samples should only differ in diagnostic indicators. Other confounding factors, such as age, sex, other biochemical indicators, and other routine blood / urine indicators, should show no significant difference between groups (p≥0.05) after statistical testing using Chisq Test, Wilcoxon, etc. The number of included samples must meet the sample size required for omics testing.

[0029] Solid-phase matrices used for protein component coupling include, but are not limited to, experimental consumables such as magnetic beads, well plates, and gels that can bind to proteins through covalent and non-covalent interactions, but it is necessary to ensure stable coupling efficiency between batches.

[0030] S102. Obtain a set of nucleic acid aptamers that bind to the above proteins based on a single round of SELEX; The single-wheel SELEX method includes, but is not limited to, classic SELEX procedures for protein immobilization such as magnetic bead SELEX (Mag-SELEX), well plate SELEX, and graphene oxide SELEX (GO-SELEX). Depending on the characteristics of the solid matrix, the procedure may be slightly modified, but it includes the following basic steps: (1) Incubation: The random library and the protein on the surface of the solid matrix are incubated in a liquid environment to allow the two to fully bind and form a protein-nucleic acid aptamer complex; (2) Separation: Based on the characteristics of the solid matrix, the protein-nucleic acid aptamer complex is collected by methods such as magnetic adsorption, filtration, and cutting; (3) Elution: The protein-nucleic acid aptamer complex is dissociated by heating, alkali treatment, photolysis, etc., and the aptamer is collected.

[0031] The randomized libraries used consist of single-stranded DNA or RNA of any length, including but not limited to artificially synthesized randomized libraries or custom libraries enriched through multiple rounds of classic SELEX. Furthermore, the randomized libraries may be chemically modified or structurally altered. Chemical modifications include, but are not limited to, biotin, fluorescent molecules, isotopes, electrochemical, enzymatic, or thiol modifications, while alterations include insertions, deletions, and mutations.

[0032] S103. Through high-throughput sequencing and omics differential analysis, combined with biological principles, candidate nucleic acid aptamers with significant enrichment differences are retained; High-throughput sequencing is used to analyze the sequence composition and enrichment trends of nucleic acid aptamer sets. Each sample yields a sequencing library containing one set of nucleic acid aptamers. To ensure sufficient data volume, the sequencing library output is no less than 1 GB. To guarantee sequencing quality, Q20% > 90%, Q30% > 80%, and the percentage of valid data > 70%. The percentage of valid data is calculated as: (Total number of reads with correct sequence length / Total number of reads in the sequencing library) × 100%.

[0033] Omics differential analysis methods are similar to transcriptome data analysis workflows, including three basic steps: data normalization and summarization, overall parallelism and differential analysis, and differential analysis. The normalization factor includes the total number of valid reads in each library and the concentration of each aptamer set. This step aims to ensure comparability of read counts for the same nucleic acid sequence in different sequencing libraries. Evaluation criteria for overall parallelism and differential analysis include the coefficient of variation (CV), Pearson correlation coefficient, and principal component analysis (PCA), used to evaluate reproducibility across parallel groups, within-group parallelism, and between-group differentials, respectively. Differential analysis methods include edgeR, DESeq2, and limma. Typically, |log2 FC Nucleic acid aptamers with a value >1 and p < 0.05 are considered to have significant enrichment differences.

[0034] S104. Obtain sufficient and real patient and control biological samples to form a large sample cohort. The inclusion rules for patient and control biological samples are the same as those described in S101, and the sample size must meet the requirements for a large sample cohort.

[0035] S105. Discover nucleic acid aptamers that can distinguish between patient and control samples by combining differential validation with a large sample cohort.

[0036] This step primarily detects whether the amount of the "protein-nucleic acid aptamer" complex formed by the binding of equal amounts of nucleic acid aptamer probes to equal amounts of biological samples shows a significant fold difference between the patient group and the control group, thus assessing the potential of the nucleic acid aptamer to distinguish between the two groups. This is achieved through absolute quantification of the nucleic acid aptamer in the complex. Absolute quantification methods include, but are not limited to, real-time quantitative PCR (qPCR), digital PCR, and other detection techniques used for absolute quantification of nucleic acid molecules. Difference analysis methods include, but are not limited to, t-tests and analysis of variance (ANOVA), with p < 0.05 considered statistically significant, and a fold change of at least 2 considered statistically significant.

[0037] Example 1 Serum screening yields a custom library for single-round SELEX: The initial random library used by the classic SELEX contains 10 13 ~10 16 The sequences are numerous, but only a small portion bind to proteins. Furthermore, artificially synthesized random libraries are single-copy libraries, making it difficult to demonstrate the enrichment differences of nucleic acid aptamers in different samples after a single round of SELEX. Therefore, in this embodiment, a mixed serum was prepared by mixing equal volumes of serum from 20 healthy individuals. This mixed serum was then subjected to five rounds of serum screening to obtain a set of nucleic acid aptamers targeting the serum proteome, which served as a customized library for a single round of SELEX in subsequent embodiments.

[0038] The process is as follows Figure 2As shown. To eliminate nucleic acid aptamer enrichment bias caused by differences in protein molecular weight and isoelectric point, and to ensure target coverage, the mixed serum was processed by two-dimensional liquid chromatography before screening. The complex blood proteome was divided into 96 fractions with similar molecular weight and isoelectric point, and each fraction was used as a separate target for serum screening. 25 μg of total protein was added to each well of a 96-well plate and allowed to stand for 1 h. The proteins were non-covalently coupled to the inner wall of the plate. The plate was thoroughly washed, and treated with 1 mg / mL bovine serum albumin (BSA) for 20 min to block remaining protein binding sites on the inner wall and reduce non-specific adsorption. A random library was then added and incubated for 1 h to allow serum proteins to fully bind to the nucleic acid aptamers. The plate was then thoroughly washed to remove unbound nucleic acid sequences. Heating at 95°C for 20 min dissociated the protein-nucleic acid aptamer complex, and the nucleic acid aptamers in the eluent were collected. The concentration of nucleic acid aptamers was detected by qPCR, and the recovery rate was calculated. Multiple copies of the nucleic acid sequence were obtained by PCR amplification, and single-stranded recovery was performed to obtain the enriched library for the next round of screening. The entire process was conducted in a 100 μL system. A total of 5 rounds of screening were performed, with the screening pressure increased by reducing the amount of library input. The library input amounts were 1400, 100, 70, 50, and 50 pmol, respectively.

[0039] The randomized library and primers used are shown in Table 1. The full-length random sequence was 78 nt, containing 20 nt fixed regions at each end and a 38 nt random region in the middle. Primers F and R were complementary to the 3' ends of the antisense and sense strands, respectively, for PCR and qPCR amplification. The 5' end of primer R was modified with biotin to recover the sense strand from the PCR product. The single-stranded DNA recovery conditions were as follows: 200 μL of 4 M NaCl and 80 μL of SA magnetic beads were added to 1 mL of PCR product and incubated for 20 min to ensure sufficient capture of the double-stranded DNA by the SA beads; the supernatant was magnetically removed, the magnetic beads were thoroughly washed, and 100 μL of 40 mM NaOH was added and incubated for 3 min to break the hydrogen bonds of the double-stranded DNA, allowing the sense strand to remain free in the liquid environment; the supernatant was magnetically collected, and 4 μL of 1 M HCl and 104 μL of 2×DPBS were added for the next round of screening.

[0040] Table 1. Randomized libraries and primers name Sequence (5'→3') Random Library TTCAGCACTCCACGCATAGC-N38-CCTATGCGTGCTACCGTGAA F TTCAGCACTCCACGCATAGC R Biotin-TTCACGGTAGCACGCATAGG The quality inspection results of each round of library enrichment trends are as follows: Figure 3 As shown. Recovery rate = Amount of nucleic acid aptamer material in the elution buffer / Amount of library added in this round × 100%. Figure 3A statistical analysis was conducted on the average recovery rate of 96 components in each round, with the error bar representing the standard deviation of the recovery rate. It was observed that the recovery rate generally showed an increasing trend with each round, indicating that aptamers with binding capacity in the library were gradually enriched. Subsequently, the changes in the binding capacity between the enriched library and the corresponding component were monitored in each round. 25 μg of protein was conjugated to each well plate and blocked with BSA. Then, 100 μL of the 600 nM enriched library of the corresponding component was added, incubated for 1 h, and the eluent was collected by heating and brought to a final volume of 50 μL. The concentration of aptamers in the eluent was absolutely quantified using qPCR. The aptamer concentration was used as the signal response value, such as... Figure 3 As shown in B, the response value is the average response value of each component in that round, and the error bar is the standard deviation. The binding ability of the enriched libraries to the corresponding component proteins in rounds 1, 3, and 5 shows a progressively increasing trend, suggesting that the enrichment frequency of protein-binding aptamers in the enriched libraries increases progressively.

[0041] High-throughput sequencing was performed on the enriched libraries from the fifth round of each component. The top 2000 reads from each library were selected, and the intersection of these reads was used to form a custom library with a capacity of approximately 16,000 reads. Microarray synthesis technology was used to obtain a small amount of library with uniform copy number, which was then amplified using emulsion amplification to obtain a sufficient amount of library with uniform copy number for a single round of SELEX screening.

[0042] Example 2 A single round of SELEX screening yielded the set of nucleic acid aptamers that bound to each sample: This embodiment uses serum samples as an example. The serum used is from patients with allergic rhinitis before and after acupuncture treatment. The diagnostic criteria for allergic rhinitis patients conform to the provisions of the "Guidelines for the Diagnosis and Treatment of Allergic Rhinitis in China (2022 Revised Edition)". The efficacy of acupuncture is evaluated according to the "Principles and Recommendations for the Diagnosis and Treatment of Allergic Rhinitis (2004 Revised Edition)", using the reduction rate of the total score of nasal symptoms and signs as the evaluation standard. A reduction rate >60% is considered significant effect, 25%~60% is considered effective, and ≤25% is considered ineffective. Significant effect and effective are considered acupuncture sensitive type, and ineffective is considered acupuncture insensitive type. The samples are divided into 4 groups: sensitive type included, insensitive type included, sensitive type excluded, and insensitive type excluded. The included group refers to the serum samples collected before acupuncture treatment, and the excluded group refers to the serum samples collected after 4 weeks of acupuncture treatment (3 times / week). A total of 118 serum samples were included, including 37 sensitive samples enrolled, 22 insensitive samples enrolled, 37 sensitive samples discharged, and 22 insensitive samples discharged.

[0043] This embodiment provides two methods for complex protein conjugation, using Protenano from Hangzhou Luomi Medical Technology Co., Ltd. TM Low-abundance protein nanobeads and NanoPro TM 1000 Protein Analyzer.

[0044] Using Protenano TM The operation procedure for a single-wheel Mag-SELEX using magnetic beads is as follows: Figure 4 As shown. Take 2 μL of 10 mg / mL magnetic beads, magnetically remove the supernatant, add 10 μL of serum sample and 10 μL of buffer, and incubate for 1 h. Then block with 1 mg / mL BSA for 20 min and thoroughly wash the magnetic beads. Add 100 μL of the custom library from Example 1 (100 nM), incubate for 1 h, and thoroughly wash the magnetic beads. Heat at 95℃ for 20 min, and collect the nucleic acid aptamer set in the supernatant. Take 2 μL for qPCR quality control, and use the remaining sample for library construction and sequencing.

[0045] Using NanoPro TM The operating procedure for a single round of nanopro-SELEX operation on the 1000 protein analyzer is as follows: Figure 5 As shown: 1) Sample injection: Dilute serum to 1 mg / mL using buffer. Prepare a premix by mixing 97.78 μL of Premix G2 and 2.22 μL of PI ladder 1. Mix 6 μL of the premix with 2 μL of blood sample and inject into the injection well.

[0046] 2) Separation: Start the instrument; proteins with different isoelectric points have different migration rates in the capillary and are distributed in different regions. 3) Immobilization: Immobilize the proteins on the inner wall of the capillary through photocrosslinking.

[0047] 4) Inject 5 μL of the customized library from Example 1 (100 nM), incubate for 1 h, and thoroughly clean the capillary.

[0048] 5) Elution and sequencing: Inject 10 μL of 40 mM NaOH for 5 min to denature and release the nucleic acid aptamers in the liquid environment, and collect the eluent. Use 2 μL for qPCR quality control, and use the remaining sample for library construction and sequencing after PCR amplification.

[0049] qPCR quality control results are as follows Figure 6 As shown in the figure, each sample point represents the Cq value of qPCR detection for each nucleic acid aptamer set. The three horizontal lines from top to bottom in each group represent the upper quartile, median, and lower quartile, respectively. It can be seen that the distribution of detection values ​​in each group basically follows a normal spindle shape, with no obvious extreme values, indicating that subsequent library construction and sequencing can proceed. During library construction, each index contains 16 sub-libraries. During PCR amplification, a different 6 nt tag sequence is added to the 5' end of primer F to distinguish different sub-libraries within the same index.

[0050] Example 3 Selection of candidate nucleic acid aptamers based on omics-based differential analysis: First, the quality of the sequencing data was analyzed. The amount of data from each index ranged from 16.39 to 17.32 G, indicating that the average amount of data from each sub-library was no less than 1 G, which meets the data requirements for subsequent analysis. The minimum Q20% was 92.72, and the minimum Q30% was 85.68, indicating that the sequencing accuracy met the standards. A valid sequence is defined as one with a full length of 78 nt, correct length and nucleotide sequence of the two 20 nt fixed regions at both ends, and correct length of the 38 nt random region in the middle. The minimum percentage of valid sequences was 84.22%, which is greater than 70%, meeting the requirements. Therefore, the sequencing data met the usage standards.

[0051] Then, a homogenization process was performed to ensure the comparability of read counts for each sequence across different libraries. The first step involved calibration using the total number of valid reads from each library. The correction factor A was calculated as the maximum total number of reads divided by the number of reads in each sub-library. Multiplying the read count of each sequence by the corresponding correction factor A completed the calibration, ensuring consistent output of valid data across sub-libraries. The second step involved calibration using the Cq values ​​obtained in Example 2. The Cq values ​​were then converted to aptamer concentrations based on a standard curve. The standard curve used in this example is: Where y is the Cq value of qPCR, and C is the concentration of nucleic acid aptamers in nM. The correction factor B = the concentration of each nucleic acid aptamer set / the minimum concentration. The number of reads for each sequence is multiplied by the corresponding correction factor B to complete the correction, so that the effective data output of each sub-library is proportional to the concentration of nucleic acid aptamers.

[0052] Then, the valid data are summarized. The first step is to remove sequences with fewer than 5 initial reads from each library, as the read count of these sequences is limited by sequencing throughput and lacks accuracy. The second step is to take the union of the remaining sequences. This is because, theoretically, blood samples from different patients with allergic rhinitis have roughly the same protein composition, with only slight differences in content; therefore, it is unreasonable for nucleic acid aptamers to exist only in certain libraries.

[0053] Overall parallelism and heterogeneity were analyzed using summary data. Three parallel groups were set up for each sample. The CV for each sequence was calculated as the standard deviation of reads / the average of reads. The average CV for each sample was the average of the CV values ​​obtained for each sequence, and the overall average CV was the average of the average CVs of all samples. The overall average CV for a single round of Mag-SELEX was 13.6%, and the overall average CV for a single round of nanopro-SELEX was 16.6%, indicating that the experimental system was stable. The average value of the parallel groups was used as the sequencing data for that sample. Within-group parallelism was evaluated by calculating the pairwise Pearson correlation coefficient. The R values ​​for the four groups obtained from a single round of Mag-SELEX were 0.91, 0.97, 0.92, and 0.95, showing strong positive correlation; the R values ​​for the four groups obtained from a single round of nanopro-SELEX were 0.70, 0.76, 0.78, and 0.72, showing good positive correlation (p < 0.05). This demonstrates good within-group parallelism of the data. Principal component analysis was used to evaluate the differences between groups, and the results were as follows: Figure 7 As shown, the total contributions of the first two principal components are 62.6% and 68.35%, respectively, both explaining more than half of the inter-sample differences. The intra-group data of both methods are basically clustered in the same region, and extreme samples located outside the cluster are removed. It can be seen that the extreme samples in a single round of the nanopro-SELEX method ( Figure 7 B) Compared to the single-round Mag-SELEX method ( Figure 7 A) More, which is consistent with the fact that the former had a weaker intragroup correlation than the latter. The overall intergroup differences were not significant, reflected in the high overlap of the regions where each group was located, suggesting that there was no significant difference in the overall blood proteomic levels between the two groups of patients, and that the key proteins that determine whether they are sensitive to rhinitis are few.

[0054] Finally, the edgeR method was used to perform pairwise difference analysis between groups, specifying |log2 FC Nucleic acid sequences with a value > 1 and p < 0.05 are considered candidate aptamers, exhibiting significant differences in binding amounts with different groups of blood samples. The number of differentially bound aptamers is shown in the figure below. Figure 8 As shown, the experimental procedure provided in this embodiment can be used to obtain candidate nucleic acid aptamers that have significant differences in binding with different groups of blood samples.

[0055] False positive results were removed by combining biological function and mathematical logic, and candidate aptamers for differential validation were selected. The selection rules are as follows: (1) Nucleic acid aptamers were classified according to the up-and-down regulation patterns of the four pairs of comparisons, and categories that did not conform to biological and mathematical logic were removed. For example, nucleic acid aptamers that showed significant differences only in one comparison and no significant differences in the other three comparisons. In the end, 22 categories were retained in a single round of Mag-SELEX and 8 categories were retained in a single round of nanopro-SELEX.

[0056] (2) Remove outliers, such as data with a low number of reads (original number of reads < 50) but a very high fold change (fold change > 5). The significant difference in this type of data may be a false positive caused by sequencing throughput limitations.

[0057] (3) In each category, 1 to 10 reads with high read count and fold change were selected as candidate nucleic acid aptamers. Among them, 77 reads were selected in a single round of Mag-SELEX (referred to as MB_01~MB_77) and 69 reads were selected in a single round of nanopro-SELEX (referred to as N_01~N_69), for a total of 146 reads.

[0058] Example 4 Validation of binding differences among alternative nucleic acid aptamers: This embodiment evaluates the ability of nucleic acid aptamers to distinguish between different groups of blood samples by analyzing the differences in the content of the "protein-nucleic acid aptamer" complexes formed by the binding of the above-mentioned candidate nucleic acid aptamers with an equal volume of blood samples. Three replicates were set up for each sample. The specific operation steps are as follows: (1) Blood sample plating: Dilute each blood sample 1000 times, take 100 μL, and couple the protein in the well plate according to the method described in Example 2. Wash thoroughly before use. (2) Incubation: Take 100 μL of each 100 nM nucleic acid aptamer and incubate with the protein for 1 h to allow them to fully bind together. Then wash thoroughly before use. (3) Heating and elution: Add 100 μL of sterile water and heat at 95℃ for 20 min to obtain nucleic acid aptamer elution buffer; (4) Absolute quantification: Detected by qPCR and converted to concentration as described in Example 3. The average concentration value of the sensitive group was taken as 1, and the relative concentration value of each sample was calculated. Relative concentration value = Detected concentration value of the sample / Average concentration value of the sensitive group.

[0059] (5) Statistical analysis: Independent samples t-test was used to compare the differences in relative concentration values ​​between groups. Where * represents p<0.05, ** represents p<0.01, *** represents p<0.001, **** represents p<0.0001, and ns represents no significant difference (p≥0.05). Based on this, a difference of not less than 2 times is considered to be significant.

[0060] Depending on the application scenario, different nucleic acid aptamer probes can be retained based on the fold change value. This embodiment aims to select nucleic acid aptamer probes that are likely to differentiate between acupuncture-sensitive and acupuncture-insensitive patients, i.e., nucleic acid aptamers with a significant fold change in sensitivity versus insensitivity for acupuncture-insensitive patients. Nucleic acid aptamer probes with this characteristic include... Figure 9 As shown.

[0061] The detection results of nucleic acid aptamer MB_04 are as follows: Figure 9 As shown in Figure A, the mean relative concentrations of the sensitive, insensitive, sensitive, and insensitive samples included in the study were 1, 0.50, 0.27, and 0.57, respectively. This indicates that the binding affinity of MB_30 to the sensitive sample was significantly higher than that to the insensitive sample, with a fold difference of 2.0, suggesting that the concentration of its target substance was higher in the serum samples of sensitive patients. Similarly, the binding affinity of MB_30 to the insensitive sample was significantly higher than that to the sensitive sample, with a fold difference of 2.1, suggesting that the concentration of its target substance was higher in the serum samples of insensitive patients. Figure 9 B). N_11 bound to insensitive enrolled samples significantly more readily than to sensitive enrolled samples, with a fold increase of 2.8-fold, suggesting that its target substance was present at higher levels in the serum samples of insensitive patients. Figure 9 C). N_56 bound to sensitive samples significantly more readily than to insensitive samples, with a fold increase of 2.0-fold, suggesting that its target substance was present at higher concentrations in the serum samples of sensitive patients. Figure 9 D).

[0062] In summary, the binding ability of the above four nucleic acid aptamers to the blood samples of sensitive and insensitive patients showed a significant fold difference, suggesting that they may serve as detection probes for predicting the efficacy of acupuncture therapy.

Claims

1. A method for discovering disease-related nucleic acid aptamers based on a single-round SELEX, characterized in that, Includes the following steps: S101. Couple the proteins in each patient and control biological sample to the surface of a solid matrix; S102. Obtain a set of nucleic acid aptamers that bind to the above proteins based on a single round of SELEX; S103. Through high-throughput sequencing and omics differential analysis, combined with biological principles, candidate nucleic acid aptamers with significant enrichment differences are retained; S104. Obtain the large sample queue; S105. Identify the nucleic acid aptamers that can distinguish between patient and control samples through binding difference verification using a large sample cohort.

2. The method according to claim 1, characterized in that, The patient and control biological samples in step S101 include one or more of whole blood, plasma, serum, urine, cells, and tissue sections.

3. The method according to claim 1, characterized in that, The solid matrix in step S101 includes one or more of magnetic beads, well plates, and gels that are bound to proteins through covalent and / or non-covalent interactions.

4. The method according to claim 3, characterized in that, The solid-phase matrix coupling method includes enriching low-abundance proteins in the sample using affinity magnetic beads or based on NanoPro. TM The 1000 protein analyzer uses the difference in isoelectric point to couple complex protein regions into capillary sections.

5. The method according to claim 1, characterized in that, The single-round SELEX method in step S102 includes the following steps: A random library of single-stranded DNA or RNA is incubated with proteins on the surface of a solid matrix in a liquid environment to allow the two to bind fully and form a "protein-nucleic acid aptamer" complex. Collect protein-nucleic acid aptamer complexes; The protein-nucleic acid aptamer complex is dissociated, and the aptamers are collected.

6. The method according to claim 1, characterized in that, In step S103, the high-throughput sequencing evaluates whether the sequencing data meets the analysis requirements based on the amount of data obtained from the sequencing, the error rate, and the percentage of valid data. For each sample, the sequencing results of the nucleic acid aptamer set obtained from the sequencing must have at least 1 G of data obtained from the sequencing, Q20% > 90%, Q30% > 80%, and the percentage of valid data > 70%, which means that the requirements are met.

7. The method according to claim 1, characterized in that, The omics differential analysis in step S103 includes the following steps: Data homogenization and summarization: The data is homogenized using the total number of valid reads and the concentration of the nucleic acid aptamer set; sequences with initial reads < 5 are removed from each sequencing library, and the remaining sequences are intersected to complete the summarization; Overall parallelism and variance analysis: The repeatability of parallel groups was evaluated using the average CV value. Three parallel groups were set up for each biological sample. An average CV < 20% indicates good repeatability. The parallelism within groups was evaluated using the Pearson correlation coefficient. R > 0.8 and p < 0.05 indicates strong positive correlation within groups. R between 0.3 and 0.8 and p < 0.05 indicates positive correlation between groups. R < 0.3 or p ≥ 0.05 indicates no correlation. Principal component analysis was used to evaluate the differences between groups, and the fact that each experimental group was distributed in different regions proved that the overall differences between groups were significant. Differential analysis: The edgeR method was used to perform differential analysis on the sequencing data of nucleic acid aptamer sets obtained from patient and control samples, specifying |log2 FC Sequences with |>1 and p<0.05 are candidate nucleic acid aptamers, showing significant differences in binding amounts with patient and control samples.

8. The method according to claim 1, characterized in that, The binding difference verification in step S105 includes the following steps: (1) After equal amounts of the same biological samples were pretreated in the same way, each sample was fully combined with an equal amount of nucleic acid aptamer in a liquid environment to obtain a "protein-nucleic acid aptamer" complex, and the complex was collected. (2) The protein-nucleic acid aptamer complex is fully dissociated, the nucleic acid aptamer is collected, and absolute quantitative detection is performed. The detection value is used as the binding amount of the nucleic acid aptamer to the sample. (3) Compare whether there is a significant difference in the binding amount of the nucleic acid aptamer to the patient and control samples; if there is a significant difference and the difference factor is not less than 2, the nucleic acid aptamer is considered to be usable as a probe.

9. The method according to claim 8, characterized in that, The absolute quantitative detection in step (2) includes quantitative real-time PCR or digital PCR.

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