Method for screening RNA aptamer

Abstract

The invention provides a method for screening an aptamer from an RNA (Ribonucleic Acid) library. According to the method, the eluent of each elution is collected, and meanwhile, a specific elution procedure is combined, so that the technical effects that any information of the RNA aptamer is not lost, the false positive rate is low, the binding capacity of the screened aptamer is high, the library preparation time is short, only one round of enrichment can be performed, the library preparation repeatability is high, and the method is suitable for an automatic mechanical arm are achieved.

Description

A method for screening RNA aptamers Technical Field

[0001] The present invention relates to the field of biotechnology, and in particular to a method for screening RNA aptamers. Background Art

[0002] Over the past 30 years, technologies such as second-generation high-throughput gene sequencing (essentially independent of the screening process and only provides sequence information), microfluidic chips (precision equipment and manual adjustment of empirical parameters by professionals), capillary electrophoresis (precision equipment and only suitable for screening aptamers that bind to large molecules), and subsequence and structure bioinformatics models (data-driven, still dependent on data quality, with high false positive rates) have further optimized and shortened the screening process for RNA aptamers. However, rapid, efficient, and universal screening technologies are still lacking.

[0003] In the face of the current global pandemic of COVID-19, RNA drug candidates under development could serve as both vaccines and therapeutics, offering high specificity and safety, minimal vulnerability to COVID-19 mutations, and requiring a short development cycle and low production costs. Furthermore, in the face of Alzheimer's disease, a disease highlighted by the long-term aging of the population, RNA drug candidates could offer advantages such as dynamic regulation, strong targeting and safety, and intelligent precision medicine.

[0004] However, existing RNA aptamer screening technology still has limitations, such as high false positive rate; non-optimal binding ability of the screened aptamers; high time cost, often requiring 10-16 rounds of repeated screening and 2-6 months of research and development; poor reproducibility; and the need for manual operation, which are obvious shortcomings that restrict the screening of RNA aptamers and their subsequent applications.

[0005] Therefore, there is an urgent need in the art for a new RNA aptamer screening method to overcome the various shortcomings of the prior art.

[0006] Summary of the Invention

[0007] The present invention aims to provide a method for screening RNA aptamers, which can reduce the false positive rate; optimize screening conditions and enhance screening ability; shorten experimental time and reduce time cost; improve the screening process and achieve repeatability; and simplify experimental operations and adapt to mechanical intelligence.

[0008] In a first aspect, the present invention provides a method for screening RNA aptamers, the method comprising the following steps:

[0009] 1) Providing an RNA aptamer library to be screened;

[0010] 2) incubating the library from step 1) with a solid support bound to the target, thereby promoting the RNA aptamers in the library to fully bind to the target;

[0011] 3) eluting the RNA aptamer bound to the target on the solid support in step 2) using a buffer gradient, and collecting the eluate from each elution;

[0012] 4) Completely eluting the RNA aptamers still retained on the solid support after step 3), and collecting the eluate as the last set of eluate;

[0013] 5) optionally concentrating and purifying the RNA aptamers in the eluate obtained in steps 3) and 4);

[0014] 6) Reverse transcribing the RNA aptamer obtained in step 5) to obtain cDNA;

[0015] 7) amplifying and performing high-throughput sequencing on the cDNA obtained in step 6) to obtain sequencing data;

[0016] 8) Analyze the sequencing data obtained in step 7) and sort the candidate RNA aptamer sequences from high to low according to their binding potential, thereby obtaining RNA aptamer sequences with high affinity.

[0017] In a preferred embodiment, providing the RNA aptamer library to be screened includes preparing the RNA aptamer library by oneself, purchasing the RNA aptamer library commercially, or obtaining the RNA aptamer library through donation from others.

[0018] In a specific embodiment, in step 2), after the RNA aptamers in the RNA aptamer library bind to the target, the solid support can be sealed to control and reduce non-specific background binding.

[0019] In a specific embodiment, the blocking is blocking the solid support with non-target specific random RNA; or blocking the solid support with target specific RNA.

[0020] In a preferred embodiment, in step 2), the solid carrier includes but is not limited to: magnetic beads and matrix.

[0021] In a preferred embodiment, the matrix includes but is not limited to: agarose gel matrix, cephalosporin beads, nitrocellulose, polyvinylidene fluoride membrane, octyl trehalose and other carrier matrices.

[0022] In a preferred embodiment, in step 2), the target is a small molecule, including but not limited to: steroids, dopamine, kanamycin, digoxin, antoxin, dinitroaniline, melamine, quinolone, aflatoxin; a macromolecule, including but not limited to: polypeptides, proteins (such as enzymes and antibodies, etc.) and complexes (proteins bound to RNA), high molecular polymers and compounds, etc.

[0023] In a specific embodiment, in step 3), the gradient elution is performed using a buffer with increasing volume, or a buffer with increasing elution strength; preferably, the elution is performed using a buffer with increasing volume.

[0024] In a preferred embodiment, the buffer with increased elution strength refers to a buffer with increased salt ion or chelating agent concentration to prevent RNA from folding to form a spatial structure.

[0025] In a specific embodiment, before gradient elution, several background elutions are performed until the number of RNA aptamer molecules contained in the eluate is no more than 1% of the high-throughput sequencing threshold.

[0026] In a preferred embodiment, the volume of the buffer for background elution should be no larger than the initial volume of the buffer used for gradient elution.

[0027] In a preferred embodiment, the elution can be static elution (discontinuous elution, collecting the entire eluate at one time) or dynamic elution (continuous elution, continuously collecting a small amount of partial eluate), preferably static elution.

[0028] In a preferred embodiment, if static elution is used, the last background elution is performed in a new container.

[0029] In a preferred embodiment, the volume of the background elution buffer may or may not be increased, preferably not increased.

[0030] In a preferred embodiment, the buffer for background elution and the buffer for gradient elution may be the same or different; preferably, they are the same.

[0031] In a preferred embodiment, the buffer used for gradient elution contains magnesium ions, preferably 5 mM magnesium ions, has a pH value below 8.5, preferably a pH value of 7-8, and a NaCl or KCl concentration between 75 mM and 200 mM.

[0032] In a specific embodiment, the number of RNA aptamer molecules contained in the eluate is made suitable for sequencing after several gradient elutions, preferably the theoretical minimum number of molecules in the library is reduced to 10 5 Next, complete elution is performed in step 4) to completely elute the RNA aptamer bound to the target on the solid support.

[0033] In a preferred embodiment, the buffer used for complete elution contains reagents capable of releasing RNA aptamers, including reagents capable of destroying the binding of the target to the solid support, and / or reagents capable of destroying the binding of the RNA aptamer to the target, and / or reagents that directly destroy the target.

[0034] In a specific embodiment, in step 7), a 0-6 nt compensation sequence is randomly inserted between the sequencing adapter and the cDNA constant region.

[0035] In a specific embodiment, in step 7), a custom-designed PhiX is introduced during the mixing of multiple samples to further compensate for the unbalanced base distribution in the constant region.

[0036] In a specific embodiment, in step 8), the binding potential refers to how quickly the enrichment level increases in each eluate, rather than simply considering the highest enrichment level.

[0037] In a specific embodiment, the binding potential is determined based on one or more of the following information about the RNA aptamer: the abundance of the RNA aptamer in each eluate, the frequency with which the RNA aptamer is detected individually in each eluate, and whether the RNA aptamer appears in subsequent eluates better than in initial eluates.

[0038] In a preferred embodiment, the above information is integrated to fit a standard curve and the binding potential of the RNA aptamer is evaluated according to the area under the curve (AUC).

[0039] In a preferred embodiment, the RNA aptamer comprises a chemically modified sequence.

[0040] In a preferred embodiment, the chemically modified sequence is a fluorine-modified sequence.

[0041] In a second aspect, the present invention provides an RNA aptamer, which is screened using the method described in the first aspect.

[0042] In a preferred embodiment, the RNA aptamer includes an RNA aptamer with a known sequence but random modifications at different bases (eg, A, U, G, C).

[0043] In a preferred embodiment, the RNA aptamer does not include conventional RNA aptamers with known sequences and no additional modifications.

[0044] In a preferred embodiment, the RNA aptamer comprises a chemically modified sequence; preferably a fluorine-modified sequence.

[0045] In a third aspect, the present invention provides an apparatus for executing the method described in the first aspect.

[0046] In a preferred embodiment, the device comprises the following modules:

[0047] 1) a preparation module, wherein the module prepares an RNA aptamer library to be screened;

[0048] 2) an incubation module, which incubates the prepared library with a solid support (magnetic beads or matrix) bound to the target;

[0049] 3) an elution and collection module, which performs gradient elution of the RNA aptamer module bound to the target on the solid support with a buffer, and collects the eluate from each elution;

[0050] 4) an optional concentration and purification module, which concentrates and purifies the RNA aptamers in the eluate;

[0051] 5) a reverse transcription module, which reverse transcribes the RNA aptamer to obtain cDNA;

[0052] 6) an amplification and high-throughput sequencing module, which performs amplification and high-throughput sequencing on the cDNA obtained above to obtain sequencing data;

[0053] 7) An analysis module, which analyzes the sequencing data and ranks the candidate RNA aptamer sequences from high to low according to their binding potential, thereby obtaining RNA aptamer sequences with high binding affinity.

[0054] In a fourth aspect, the present invention provides a biochip, comprising the RNA aptamer according to the second aspect.

[0055] In a fifth aspect, the present invention provides a method for manufacturing a biochip, comprising the following steps:

[0056] 1) Screening and obtaining RNA aptamers using the method described in the first aspect; and

[0057] 2) preparing a biochip using the RNA aptamers screened in step 1).

[0058] In a sixth aspect, the present invention provides a pharmaceutical composition comprising the RNA aptamer described in the second aspect and a pharmaceutically acceptable excipient or drug delivery carrier.

[0059] In a seventh aspect, the present invention provides a drug delivery vector, to which the RNA aptamer described in the second aspect is connected.

[0060] In a preferred embodiment, the drug delivery vehicle is a liposome.

[0061] In a specific embodiment, if there are specific recognition receptors on the cell surface, the RNA aptamer of the present invention can be glued or connected to a delivery carrier (such as nanoliposomes), so that the drug encapsulated in the carrier can be specifically delivered to the designated cells.

[0062] In an eighth aspect, the present invention provides a diagnostic reagent comprising the RNA aptamer described in the second aspect and other auxiliary reagents required for diagnosis.

[0063] In a ninth aspect, the present invention provides use of RNA aptamers screened and obtained by the method of the first aspect in preparing a biochip, a pharmaceutical composition or a diagnostic reagent.

[0064] It should be understood that within the scope of the present invention, the above-mentioned technical features of the present invention and the technical features described in detail below (such as in the embodiments) can be combined with each other to form new or preferred technical solutions. Due to space limitations, they will not be listed here one by one. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 shows the construction and modeling analysis of the RNA library of the present invention. Figure a shows the screening RNA and sequencing library construction of the present invention. First, a random RNA library source is incubated with a targeting molecule attached to magnetic beads. The mixture of RNA-bound targeting molecules is washed sequentially with increasing volumes of the same binding buffer, and the washes are collected, referred to as groups 1-10 (g1-10). The mixture is then subjected to a final elution (group 11, g11) using the corresponding chemical reagent or enzyme to completely detach the strongly bound targeting RNA from the magnetic beads. The purified RNA from g1-11 is further reverse transcribed, amplified by offset PCR, and amplified by Illumina PCR. Finally, custom PhiX is added before sequencing to balance the base distribution of the library. Figure b shows the sequencing data mining of the high-affinity aptamer of the present invention. The raw sequencing sequence is preprocessed into a 67nt core region. After data cleaning, the sequences are counted and merged into the same data frame. Sequences in each non-initial group (g2-11 relative to g1) are normalized according to the default initial gamma baseline, and the multiple ratio weights are adjusted. The gamma change rate (gf) of sequences in each change ratio group is represented by the area under the curve (AUC). The ranking model can be further refined based on the subsequence characteristics of the top-ranked sequences and their enrichment pathways in each group. Finally, the aptamer sequences with the highest AUC values ​​are selected for downstream functional applications.

[0066] Figure 2 shows the construction features of the RNA library of the present invention. Wherein, a is the sequence composition of the random RNA library source of the present invention. The RNA sequence (103nt) includes, from the 5'-end to the 3'-end, the primer A binding region (19nt, purple square, sequence marked below), the left arm random region (N26, 26nt), the pre-circular (L12, 12nt) region, the right arm random region (N26, 26nt), and the primer B binding region (20nt, dark green square, sequence marked below). b is the reverse transcribed single-stranded cDNA template sequence used for offset PCR amplification. The dark blue and purple shaded sequences represent the partial binding regions with primer B and primer A, respectively. c is the sequence composition of the dsDNA library of the present invention for sequencing. The RNA sequence composed of the fixed sequence pre-circular (L12) region and two random 26nt (N26) regions is reverse complementary to the dsDNA. D is two versions of the offsetPCR multiple primer combination. The forward primer ("Frw") includes a 5'-end sequencing adapter sequence (grey shading), a 0-6nt compensatory sequence (orange letters), and a portion of the primer B region sequence (dark green letters), while the reverse primer ("Rev") includes a 3'-end sequencing adapter sequence (green shading), a 0-6nt compensatory sequence (orange letters), and a portion of the primer A region sequence (purple letters). Version 1 (V1) compensatory primers of this design are 2nt longer than version 2 (V2) compensatory primers. e is a custom-designed PhiX sequence specifically designed by the present invention to balance the uneven distribution of bases. The custom-designed PhiX includes sequencing adapter sequences at the 5' and 3' ends and random nucleotides (indicated by "N"). Nucleotides shaded in light blue are used to compensate for base deviation. F is the electrophoresis analysis of offset PCR and Illuminal PCR products by Bioanlyzerd. The x-axis represents the length of dsDNA, while the y-axis corresponds to the intensity of the fluorescent signal. The abbreviations "V1" and "V2" are the same as those in Figure d, while "52.5C", "51C" and "68.5C" represent PCR annealing temperatures. g is a compensation sequence distribution diagram of the sequencing library. The x-axis represents the length of the compensation sequence identified from the original reads, and the y-axis represents the percentage of compensation sequences with a specified length in the library. The torch-shaped box plot consists of compensation sequences with a specified length in 11 groups (n=11) of the present invention. "RLA", "RLB" and "RLC" are the abbreviations of the "+None", "tRNA", and "cRNA" background closure systems applied to silicon rhodan in the RNA library of the present invention. Similarly, "NLA", "NLB" and "NLC" are abbreviations of the corresponding background closure systems applied to the new coronavirus replicase nsp12. The dotted line represents the ideal percentage of compensation sequences with an average distribution (14.28%, 100 / 7). h is a percentage distribution diagram of the corresponding data after processing of the library sequence.The x-axis represents the process from raw sequence number ("raw") to offset sequence trimming ("after_offset") to pre-loop region establishment ("after_bridge") to unknown sequence signal processing ("after_N"), while the y-axis represents the percentage of sequences that passed this process. The torch-shaped box plots are composed of the percentage of sequences from the 11 groups (n=11) of the present invention that met the selection criteria in the corresponding processing steps. The abbreviations are the same as those in Figure f. The dotted line represents the 94% percentage.

[0067] Figure 3 shows a comparison of the systematic gradient reproducibility (SGRELI) capabilities of enriched ligands of the present invention and the prior art. Wherein, a is the enrichment abundance trend of three representative high-affinity aptamers in each sub-library (group (g) / round (r)) in the present invention and the prior art. RLA, RLB, and RLC are the abbreviations of the libraries of the present invention, the same as in Figure 2g, while RC is the abbreviation of the conventional library. Lines of different colors represent the enrichment trends of different aptamers, and the points on each line represent the abundance of the corresponding aptamer in a given sub-library. The arrows indicate the abundance change trend from the second-to-last / third-to-last sub-library to the last sub-library. The x-axis represents the order of the sub-libraries, and the y-axis is the relative sequence abundance (per million qualified sequences (RPM)). b is the average Pearson similarity coefficient of the subsequences of the enriched sequences from the sub-libraries of the present invention / prior art and the corresponding subsequences from the Dope directed random library validation dataset. The abbreviations, arrows, and x-axis of the sub-libraries are the same as in Figure 2a. The y-axis represents the average Pearson correlation coefficient, and the gray dashed line represents the reference value of 0.6. The solid lines of different colors represent the number of sequences at different enrichment levels ("t1k" represents the top 1,000, "t10k" represents the top 10,000, "t100k" represents the top 100,000, and "all" represents all sequences) used for the subsequence calculation, while the points within the lines represent the average Pearson correlation coefficient for each validation data set calculated for a specified subelution group and using a specified number of enriched sequences. The first row of analyses is based on a subsequence length of 6 nt ("n6" in the legend), while the second row uses a subsequence length of 10 nt ("n10" in the legend).

[0068] Figure 4 shows the maximum threshold and trend characteristics of SGRELI in the present invention. Among them, a shows the abundance correlation of the sub-features (6nt) of the top 10,000 sequences enriched in the sub-library of the present invention / prior art and the sub-library of the Dope directed random validation dataset. The x-axis represents the log 10 logarithmic transformed relative abundance of the sub-features of the present invention / conventional technology, while the y-axis represents the relative abundance of the Dope validation dataset. Among them, the blue points represent the correlation calculated based on the seq A directed validation library, while the red and green points represent the correlation based on the seq B and seq C directed random libraries, respectively. The legend shows the Pearson correlation coefficient of all points between the present invention / conventional technology and the corresponding doping library source ("pA" represents the directed seq A library, "pB" and "pC" represent the directed random seq B and seq C libraries, respectively). The abbreviations of the sub-libraries ("gx" and "rx") and libraries ("RLX" and "RC") are the same as those in Figure 3a. b shows the same experiment and analysis as Figure 3b, but using 5nt, 7nt, 8nt, and 9nt as the length of the subsequence for correlation analysis. C shows the average Pearson correlation coefficient of subsequences of different lengths in the first 10,000 sequences in the sub-libraries of the present invention / prior art and the Dope directed random validation data set. The abbreviations of the sub-libraries ("gx" and "rx"), libraries ("RLX" and "RC"), x-axis, y-axis, and arrows are the same as in Figure 3b. Lines of different colors represent subsequence calculations based on the corresponding library sources, and the points in the lines are the average Pearson correlation coefficients between the specified sub-library and each validation library. "x-gram" means that the x nt length of the subsequence is applied to the Pearson correlation calculation. D shows the gamma baseline library. Lines of different colors (gamma>=1) and dotted lines (gamma<1) represent the weighted baselines for each fold comparison (referring to Group 1). The y-axis represents the expected enrichment weight.

[0069] Figure 5 shows the application of high-affinity silirhodamine RNA aptamers screened by the present invention in cell-stimulated fluorescence imaging. A shows the overlap of the top 25 RNA aptamers in three silirhodamine (SiR) libraries. The percentage represents the proportion of RNA aptamers that bind to and activate fluorescent silirhodamine (turn on). B shows the percentage of overlap of the three SiR libraries based on the number of aptamers ranked at the top. The x-axis represents the number of RNA aptamers selected from each library during the analysis, while the y-axis represents the percentage. The green line represents the percentage of RNA aptamers that appear in all three libraries, while orange and blue represent those that appear in only two libraries and a single library, respectively. C shows the KD curves of the top-ranked high-affinity aptamers RLB2 and RLB15. 50nM SiR-PEG2-NH2 probe was incubated with different concentrations of RNA aptamers. The y-axis represents the measured relative fluorescence intensity. D shows the turn-on fluorescence intensity multiples of the top 25 RNA aptamers in the RLB library. The x-axis represents the top "N" RNA aptamers (ranked in descending order, red columns), pure dye reference (blue columns), and pure buffer (gray columns). The column height represents the fold change in fluorescence intensity, with the signal intensity change of the pure dye as a unit of 1 (shown by the dotted line). The error bars are mean ± standard deviation. e shows that the library of the present invention activates a higher fluorescence fold than the top-ranked RNA aptamers from the prior art library. The relative fluorescence fold change of the top-ranked aptamers of the present invention from RLA (blue, n=25), RLB (orange, n=25), and RLC (green, n=25) is compared with the top aptamers from the conventional RC (red, n=42). f shows the rank distribution of SiR-activated and -activated RNA aptamers in the library of the present invention. The y-axis represents the rank distribution of RNA aptamers in the corresponding library. The purple boxes (n=20) and gray boxes (n=21) represent the activated and -activated RNA aptamer groups, respectively. Figure g shows that the RLB aptamer has a higher fluorescence quantum yield than SiRA, making it more suitable for RNA imaging in living HEK237T cells. In the presence of 200 nM SiR-PEG-NH2 dye, the target cell RNA is visualized in red, while the nuclear region is visualized in blue by Hoechst dye.

[0070] Figure 6 shows the characteristic details of the screening RNA silicon rhodamine aptamers of the present invention. Among them, a shows that SiRs with large gamma values ​​exhibit relatively high screening accuracy. The F1 score is calculated by evaluating the top-ranked sequences in the library of the present invention (predicted "binding") and the rest (predicted "non-binding"), with reference to the top-ranked sequences in the directed random Dope validation library (actual "binding") and the rest (actual "non-binding"). The highest F1 (used to adjust for enrichment trends) and the ruler sequence percentage (used to determine the position of reweighting) within the baseline boundary value range (0-0.25, used to separate the true "binding" and true "non-binding" buckets) are plotted on the heat map. The maximum F1 for all given combinations is indicated by white boxes and numbers in the heat map, while the F1 score based on gamma 1.0 is indicated in red. b shows the details of the effect of changing the gamma value on SiR ranking accuracy based on a fixed ruler sequence percentage (0.01) within the ranking baseline boundary range. The top row represents the effect of the entire baseline range, while the bottom represents the most valuable high-ranking baseline range (0-0.02). Different gamma values ​​are represented by different colors and line formats in the figure. The Sankey diagram in c shows the enrichment path of the SiR aptamer with the highest AUC. The colored bucket "A" represents the top 0.01% of sequences in the specified sub-library, "B" represents the top 0.01-0.05%, and "C" represents "" represents the top 0.05-0.1%, "D" represents the top 0.1-0.5%, "E" represents the top 0.5-1%, "F" represents the top 1-5%, "G" represents the top 5-10%, "H" represents the top 10-50%, "I" represents the top 50-100%, and "J" represents not present in the current sublibrary. The bucket size is linearly related to the number of sequences within the corresponding highest ratio range, and the flow size is also linearly related to the number of sequences between nodes. d shows the distribution of gamma-corrected AUC values ​​for SiRs. To allow cross-comparison between the three SiR libraries, the maximum AUC value was scaled to 1.0. The height of the bar indicates the number of sequences within the specified AUC range. e shows the increasing trend of normalized ranking factor values ​​for three high-affinity SiR aptamers. The x-axis represents the subclasses depicted by the gamma-corrected ratio change (gf) as in Figure 1a. The colored lines represent the enrichment trends for the corresponding libraries, and the points on the lines represent the ranking factor values ​​for the specified subclasses. The specific AUC values ​​are provided in the legend.

[0071] Figure 7 shows the high-affinity SARS-CoV-2 replicase RNA aptamers screened by the present invention and their application in inhibiting RNA replication. Figure a shows the overlapping intersection of the top 25 RNA aptamers in three libraries of SARS-CoV-2 replicase (nsp12). The percentages in the figure represent the proportion of high-affinity RNA aptamers. Figure b shows the same experimental and analysis process as Figure 5b, but using the nsp12 library as the data source. Figure c shows the binding details between the RNA aptamers of the present invention and the nsp12 protein characterized by biomembrane interferometry (BLI). The binding process (left) and the dissociation process (right) are separated by vertical dashed lines. Curves of different colors represent the measurement conditions using the corresponding RNA concentration. Figure d shows the KD values ​​of 77 randomly selected NLB aptamers of the present invention and their statistics in library ranking. The horizontal and vertical histograms represent the distribution of library ranking and KD values, respectively. The dark green points (n=17) indicate that the KD is multiple measurement data through three independent repetitions, while the light green points (n=60) are single measurement data through two independent repetitions. Numbers near the dots indicate their ranking within the library. The horizontal dashed line indicates a KD of 10 nM, while the gray percentage values ​​indicate the proportion of aptamers above and below this limit. (e) shows the ranking distribution of the high-affinity RNA aptamers from Figure 7d in the present invention and conventional libraries. NCA (n=68), NCB (n=66), and NCC (n=66) are libraries of nsp12 screened using conventional methods for 11 rounds. Their blocking system is the same as that of the present invention's NLA (n=77), NLB (n=77), and NLC (n=77) libraries. (f) and (g) show that the addition of 3'-end-blocked RNA aptamers of the present invention to the nsp12 / 7 / 8 (RdRp) replicase complex effectively inhibits elongation. The concentration ratios of RNA template: aptamer: nsp12 / 7 / 8 were 2.5 μM: 1.25 μM: 1.25 μM. RNA was separated by denaturing PAGE electrophoresis and visualized (g). Figure f shows the corresponding statistical values ​​of three independent replicates. Error bars represent mean ± standard deviation. Figure h and i show the inhibitory effect of the aptamers of the present invention with 3'-end blocking, visualized (Figure h) and quantified (Figure i). Error bars represent mean ± standard deviation.

[0072] Figure 8 shows the characteristic details of the present invention for screening RNA aptamers for application in the novel coronavirus replicase nsp12 and the inhibitory effect of 3'-end modification on the polymerase. Among them, a shows that nsp12 with a small gamma value has a relatively high screening accuracy. The analysis process is the same as Figure 6a, but the nsp12 library is used for evaluation, and the last round of sequence abundance of the nsp12 traditional library is used as a reference for verification. b is the same as the analysis process in Figure 6b, but the nsp12 library is used for evaluation, and the last round of sequence abundance of the nsp12 traditional library is used as a reference for verification, and the analysis baseline boundary range uses 0-0.2. c is the same analysis procedure as Figure 6c, but the nsp12 library is used for evaluation. Colored buckets ("A") represent sequences ranked in the top 0.00001% of the specified sublibrary, "B" represents the top 0.0001-0.0005%, "C" represents the top 0.0005-0.001%, "D" represents the top 0.001-0.005%, "E" represents the top 0.005-0.01%, "F" represents the top 0.01-0.1%, "G" represents the top 0.1-1%, "H" represents the top 1-10%, "I" represents the top 10-100%, and "J" represents sequences not present in the current sublibrary. The analysis procedure in Figure d is identical to that in Figure 6d, but using the nsp12 library for comparison. The analysis procedure in e is identical to that in Figure 6e, but using the nsp12 RNA aptamer. In f, the BLI KD assay was performed using a lower RNA aptamer concentration, consistent with the higher concentration. The experimental and analytical procedures are identical to those in Figure 5c, but using a lower RNA concentration for measurement. Figure g shows the low background signal of RNA aptamers in the BLI KD assay. The same experimental and analytical procedures as Figure 5c were used, but using a system without added protein (left panel) or a randomly selected RNAI as a reference (right panel). In Figure h, incubation of the RNA aptamers of the present invention with native nsp12 and RdRp resulted in observable elongation inhibition. The concentration ratios of RNA template:aptamer:nsp12 / 7 / 8 were 2.5 μM:5 μM:2.5 μM. RNA isolation and visualization were the same as in Figure 7g. In Figure i, blocking the 3'-end of the RNA aptamers of the present invention increased the inhibitory effect on RdRp elongation activity. The ratio of inducer was used. In the inhibition assay, the ratios of RNA template (2.5 μM) to aptamer added native ("o") or blocked ("b") were 2, 1, 0.5, 0.25, and 0.125, respectively. The concentration of nsp12 / 7 / 8 was 2.5 μM. RNA isolation and visualization were the same as in Figure 7g.

[0073] Figure 9 shows the in vitro inhibition of HIV-1 reverse transcriptase by chemically fluorinated RNA aptamers (pentose 2'-end) screened by the present invention. Panel a shows the inhibition of HIV-1 reverse transcriptase by RNA aptamers obtained from three different screening libraries. The libraries include RT-F ("RTF", a single library containing 30 random sequences ("30F") in the RNA, with fluorinated C and U), RT-FF ("RT-FF", a mixed library containing either 30 random sequences ("30F") or 20 random sequences ("20F") in the RNA, with both sequences fluorinated C and U), and RT-FN ("30FN", a mixed library containing both 30 random sequences ("30F") and 20 random sequences ("20F") in the RNA, with only the 30F library RNA fluorinated C and U, while the 20F library RNA was not fluorinated). "ubique" refers to RNA aptamers that are highly recurring in the library, while the reference sequence 70N89 is a published nucleic acid aptamer that inhibits HIV-1 replicase. In the measurement system, the 5-terminus of the DNA is labeled with Cy3 for instrument measurement and visualization. The reaction system used a DNA template:DNA primer:RNA aptamer:HIV replicase (p66) concentration ratio of 100nM:100nM:10nM:60nM. Panel b shows the percentage of RNA aptamer inhibition of replication, a visualization of panel a. The ratio was calculated as the percentage of the unextended band intensity to the total intensity of the extended and unextended bands. The results were then normalized to the positive control ("PC") and negative control ("-Enzyme"). The experiment was repeated three times. DETAILED DESCRIPTION

[0074] The inventors conducted extensive and in-depth research on RNA aptamer screening methods. During this exploration, they discovered that collecting the eluate from each elution can preserve any information about the RNA aptamer, thereby combining all "background" wash information to determine the systemic gradient reproducibility (SGRELI) of enriched aptamers. The method of the present invention achieves a low false positive rate, screened aptamers with strong binding ability, shortens library preparation time, allows for a single round of enrichment, provides highly reproducible library preparation, and is compatible with automated robotic arms. This is the basis for the completion of the present invention.

[0075] RNA aptamers and screening methods thereof

[0076] The terms "RNA aptamer" and "RNA ligand" are used herein synonymously, referring to RNA molecules that can interact with various biological and chemical targets, thereby regulating their function. Similar to antibodies, short, single-stranded RNA aptamers are artificially selected to specifically recognize and bind to their targets by folding into a specific three-dimensional structure.

[0077] Commonly used aptamer screening techniques in this field primarily involve iteratively screening and enriching RNA aptamers in RNA libraries. This technology has promoted the widespread application of RNA aptamers, such as super-resolution RNA imaging in living cells, SARS-CoV-2 RNA detection, and spike protein blocking. However, researchers typically need to perform 8-16 rounds of repeated screening, followed by extensive Sanger sequencing, which takes anywhere from weeks to months. Although counterselection, second-generation high-throughput sequencing (NGS), capillary electrophoresis, and microfluidic chip separation have reduced the number of RNA screening iterations and improved binding specificity, there is still a lack of methods for rapidly screening high-affinity RNA aptamers in a single round.

[0078] The inventors developed a rapid screening method for high-affinity RNA aptamers, applying it to fluorescent silica rhodamine (0.6 kDa) for live-cell RNA imaging and also to the SARS-CoV-2 polymerase nsp12 (~110 kDa) for inhibition of RNA-dependent RNA polymerase (RdRp) replication. After a five-hour wet-bed screening of RNA aptamers, NGS libraries of 11 gradient-washed RNA solutions were constructed within a single day and sequenced and analyzed using mathematical modeling. Unlike other high-affinity selection methods that rely on RNA aptamer abundance in the final enrichment eluate, the present method incorporates all "background" wash information to determine the systemic gradient reproducibility (SGRELI) of the enriched aptamer. The RNA aptamers screened using this method are high-affinity, potent, and reproducible. Silica rhodamine-activated fluorescence and SARS-CoV-2 RNA polymerase activity validate the successful application of these RNA aptamers for target functional regulation.

[0079] Specifically, the method of the present invention combines wet and dry experiments. The end-to-end method of the present invention consists of two parts: wet and dry experiments (Figure 1a, b). In order to ensure sufficient diversity of the library, ~2x10 14 Random RNA molecules (Figure 2a) were used to screen aptamers. Biotin-labeled target molecules or His-labeled target molecules were captured by streptavidin and Ni-NTA magnetic beads, respectively. In order to systematically evaluate the nonspecific binding of the method of the present invention, this study conducted a parallel comparison of three magnetic bead blocking systems: type A (no blocking), type B (tRNA blocking) and type C (RNA blocking with known binding ability). Within 1 hour, RNA with different binding and dissociation abilities were harvested from 11 groups by increasing the washing pressure (Figure 1a). The RNA selected from each group was reverse transcribed into single-stranded cDNA (Figure 2b).

[0080] Because this cDNA contains constant region sequences at the 5' / 3' ends and in the central pre-circular region, it is primarily used for PCR primer binding. However, each sequencing cluster produces the same fluorescent signal at the same base position. This can lead to large areas of single fluorescent overexposure in Illumina high-throughput sequencing, thereby covering other signals. To address this base imbalance, offset PCR was designed to randomly insert 0-6 nt compensation sequences between the sequencing adapter and the cDNA constant region (Figure 2c). As a result, the bases from the seven different length cDNAs were sequenced accordingly, and the base composition was balanced (Figures 2d and 2f). The balanced dsDNAs were then ligated to the sequencing primers and sample tags via PCR. During the mixing of multiple samples, a custom-designed PhiX was also introduced to further compensate for the unbalanced base distribution in the constant region (Figures 2e and 2g).

[0081] When sequencing is complete and the dry experiment phase begins, the raw sequences for each group are cleaned and merged to obtain a high-quality data framework (Figure 2h). Data conversion, ranking modeling, and parameter adjustment are then performed, and finally, the candidate RNA aptamer sequences are ranked from high to low based on their binding potential. The entire analysis process takes approximately 30 minutes (Figure 1b).

[0082] Compared with conventional methods, SGRELI makes the method of the present invention more advantageous. The conventional procedure washes away non-specifically bound ligands multiple times, and then collects the final eluate as a collection of the strongest binding ligands. Unlike the conventional procedure, the method of the present invention collects information from all eluates, which are usually discarded and ignored in the conventional procedure. In order to compare the enrichment performance of the method of the present invention and the conventional method for high-affinity RNA inducers, this article generated 7 SiR-based deep sequencing libraries: a conventional library (RC) derived from previous work, three libraries of the present invention using magnetic bead closed systems type A (RLA), type B (RLB) and type C (RLC), and three validation libraries based on directed random generation of sequences of known SiR-binding aptamers seqA, seqB and seqC (Table 1).

[0083] In the 11 groups of the present invention's single-round method, the enrichment trends of aptamers seqA (KD 430 nM) and seqC (KD 1456 nM) were similar to those in the final 11 rounds of the conventional method, but seqB (KD 25 nM) was specifically discovered in the present method (Figure 3a). This demonstrates the effectiveness of the present method for high-affinity RNA aptamers. Consistently, in the final elution groups of the present method, the enrichment abundance of all three aptamers initially increased and then decreased, whereas theoretically, the last group should have the strongest enrichment effect. This sudden drop suggests that the RNA ligands harvested from the elution step may not be the optimal enriched ligand group, contaminated with more background. To eliminate bias caused by small sample size analysis, the inventors compared the top enriched sub-features of sequences from the present method and the conventional method using the validation library as a reference. As the number of selection groups or rounds increased, the similarity between the most enriched sequences from the present method and the conventional method gradually increased (Figures 3b and 4a). It is worth noting that the peak of the sub-feature similarity of the method of the present invention occurs before the final elution step and is higher than that of the library of the conventional method, regardless of the length of the sub-feature (Figure 3b and Figure 4c). All other analyses of the similarity of subsequence groups of different lengths also found that the similarity of the method of the present invention suddenly dropped in the final elution step (Figure 4b). Therefore, the gamma baseline is used here to simulate this enrichment trend of the method of the present invention (Figure 4d). Putting these sudden drops in features and the higher sub-feature similarity proof together, the method of the present invention repeatedly and gradiently observed enriched aptamers from the eluates of those conventional methods, and the enriched aptamers had a lower background signal.

[0084] The present inventors studied the effect of RNA silicon rhodamine aptamers obtained by the method of the present invention on turning on the fluorescence signal of the dye.

[0085] To study the performance of enriching high-quality aptamers, in this paper, the SGRELI ranking model was analyzed with 380 hyperparameter gamma values and scale quantile combinations in three SiR libraries of the present invention. Taking the validation library as a reference, the ranking order of these sequences in the library of the present invention and the conventional library was compared. According to the best f1 score, RLC(61)>RLB(59)≥RLA(51)>RC(36), the model with a medium gamma value (4) produced higher accuracy in predicting the ranking order (Figure 6a). In addition, the scale quantile had only a minor impact on improving the prediction accuracy. To eliminate the bias brought by different sorting ranges in the validation library, the inventor further analyzed the prediction accuracy of hundreds of different bins, with the range being (abundance ranking top 0.00025 - 0.25). Similarly, in the small range of the top rankings, the accuracy of the predicted rank order was the same as the best f1 score order in the global range (Figure 6b). To optimize the generalization ability, we analyzed the library using the default gamma value (1.0), which performed well in both the method of the present invention and the conventional method. Comparing the enrichment routes of the top-ranked sequences in the library of the method of the present invention, the first group to completely cover the top-ranked sequences was the RLA library, followed by the RLB and RLC libraries (Figure 6c). This also conforms to the order of systematically combining competitors, i.e., no occlusion < tRNA occlusion < known binding - RNA occlusion. In addition, it was noted that the bins of the predicted top-ranked sequences in the RLB library were much denser than those in the RLA and RLC libraries (Figure 6d). At the same time, the RLB library provided a larger AUC score for their rankings (Figure 6e). This means that the RLB library may have better enrichment ability. [[ID=!]]

[0086] Due to limited manpower, only a small fraction of aptamers are typically selected for downstream validation, making it important to understand the performance of the top-ranked aptamers in all three libraries of this invention. Here, 100% of the top 25 aptamers for RLB were found to bind to SiR and activate fluorescence, compared to 52% and 68% for RLA and RLB, respectively (Figure 3a). Most aptamers for RLB were also found for RLA and RLC (Figure 5b), with similar rankings (Figure 5f). Although aptamers can also bind to SiR without activating dye fluorescence, since the primary goal of this application was to screen for aptamers that activate fluorescence, aptamers that do not activate dye fluorescence were not analyzed separately. The two most promising aptamers, RLB7 and RLB15, had a KD approximately 2-fold lower than the best reported aptamer (SiRA, KD = 430 ± 70 nM, ~7-fold fluorescence activation) (Figure 5c) and exhibited up to 20% increased fluorescence yield (Figure 5d). Based on the performance comparison of aptamer-activated fluorescence, RLB is the most abundant aptamer library for activating fluorescence signals, followed by RLC, RLA and RC (Figure 5e). In addition, aptamers with opening capabilities rank higher than aptamers without opening capabilities. Since SiRA ranks around 1000 in all libraries of the present invention, the RLB aptamers in the top 1000 may contain more other applicable aptamers. The RLB aptamer was further used here for live cell RNA imaging. It showed a higher and cleaner signal than SiRA (Figure 5g). In summary, method x of the present invention established high-quality aptamers, activated SiR and was applied to live cell RNA imaging.

[0087] The inventors also verified the ability of the RNA novel coronavirus replicase aptamer obtained by the method of the present invention to inhibit enzyme activity.

[0088] The pandemic of respiratory illness caused by SARS-CoV-2 necessitates the urgent need to develop and update effective drugs to combat the constantly mutating virus. The novel coronavirus utilizes the RdRp complex to replicate its RNA genome and transcribe genes. Rather than blocking the spike protein to combat viral infection, the use of high-affinity aptamers that compete with the natural substrates of the RdRp could potentially disable viral replication.

[0089] In order to explore the correctness of this hypothesis, the inventors first applied the method of the present invention and the conventional method to the viral catalytic replicase nsp12 to discover high-quality aptamers. Thus, three nsp12 libraries of the present invention were generated, namely, magnetic bead closed systems of type A (NLA), type B (NLB) and type C (NLC). At the same time, three conventional nsp12 libraries were also established, namely, type A (NCA), type B (NCB) and type C (NCC), with the same closed system. Similar to the SiR library of the present invention, compared with the conventional library NCA (54), NLA (75), NLB (71) and NLC (73) had higher f1 scores (Figure 8a). Similarly, the prediction of the top-ranked aptamers using the default gamma value (1.0) also performed well (Figure 8b). According to the enrichment route of each group of top-ranked aptamers in the present invention, the difference in enrichment ability was small and in the order of NLC>NLB≥NLA (Figure 8c). Furthermore, despite similar AUC scores for NLB and NLC (Figure 8e), the NLB library still possessed a higher density of top predicted aptamer sequences than the other libraries (Figure 8d). Interestingly, a high proportion of the top-ranked aptamers bound to nsp12 and were found on all three aptamers (Figures 7a and 7b). The top-ranked aptamer, NLB2, showed a K D 827 pM, while the lower-ranked aptamer NLB113 even had a K D The results were as follows: the binding affinity of the top aptamers was 32 pM (Figure 7c and Figure 8f). In contrast, the RNA background control system without nsp12 and the background control system with random RNA and nsp12 did not show any obvious signal (Figure 8g). To further evaluate the binding ability of the top aptamers, 86 of the top 200 compounds were randomly selected from the NLB library. More than 90% of them were found to have strong binding affinity to nsp12, and more than half of these binding aptamers had a K D The affinity of these high-affinity aptamers in the present invention was lower than 10 nM ( FIG. 7 d ). These high-affinity aptamers ranked higher in the present invention than in the conventional library ( FIG. 7 e ). This indicates that the method of the present invention can more effectively enrich high-quality aptamers than the traditional method.

[0090] The inventors also investigated the inhibitory effects of these high-affinity aptamers by competing with RNA substrates for the RdRp extension reaction. NLB2 exhibited a higher inhibitory effect than other aptamers (Figure 8h). Significantly, oxidative blocking of the 3'-ends of RNA aptamers significantly enhanced their inhibitory effects (Figure 8i). Compared to the NLB2 aptamer, NLB30 exhibited lower inhibitory effects before 3'-end blocking but higher inhibitory effects after blocking. This shift in blocking effects suggests that RNA aptamers may bind to nsp12 and / or the entire RdRp complex at different locations, but their primary inhibitory function is partially dependent on the RNA 3'-end. Furthermore, when the number of RNA aptamer molecules is less than that of the nsp12 protein, the complete inhibitory effect is weakened. This suggests that the 3'-end-blocked RNA inducer interacts with nsp12 in a 1:1 ratio. Furthermore, several RNA aptamers (such as NLB30) inhibited viral replication extension reactions by more than 98%, while control RNA did not (Figures 7f and 7g). Moreover, this strong inhibitory effect is consistent over a period of time (Figures 7h and 7i). Therefore, based on the inhibitory effect of RNA-nsp12, the method of the present invention can quickly screen high-affinity aptamers to inhibit the replication of rapidly mutating new coronaviruses.

[0091] In addition, considering that chemical modifications such as fluorination can improve the stability of RNA, the present invention has also verified the screening of unconventional RNA aptamers. The present invention is based on HIV-1 replicase as a screening target, and has established three different screening libraries, including a single-length library ("RT-F") and a mixed-length library ("RT-FF", "RT-FN"). The top 12 RNA aptamers screened from these libraries can effectively inhibit the replication efficiency of HIV-1 reverse transcriptase (Figure 9), and other aptamers containing reported "CGGG" paired inhibitory functional domains also have inhibitory effects. Therefore, this method has a reliable screening effect for RNA chemical modification. In a specific embodiment, the RNA aptamer of the present invention may include a chemically modified sequence. In a preferred embodiment, the chemically modified sequence is a fluorine-modified sequence.

[0092] In a specific embodiment, the present invention provides a method for screening RNA aptamers, comprising the following steps:

[0093] 1) Providing an RNA aptamer library to be screened;

[0094] 2) incubating the library from step 1) with a solid support bound to the target, thereby promoting the RNA aptamers in the library to fully bind to the target;

[0095] 3) eluting the RNA aptamer bound to the target on the solid support in step 2) using a buffer gradient, and collecting the eluate from each elution;

[0096] 4) Completely eluting the RNA aptamers still retained on the solid support after step 3), and collecting the eluate as the last set of eluate;

[0097] 5) optionally concentrating and purifying the RNA aptamers in the eluate obtained in steps 3) and 4);

[0098] 6) Reverse transcribing the RNA aptamer obtained in step 5) to obtain cDNA;

[0099] 7) amplifying and performing high-throughput sequencing on the cDNA obtained in step 6) to obtain sequencing data;

[0100] 8) Analyze the sequencing data obtained in step 7) and sort the candidate RNA aptamer sequences from high to low according to their binding potential, thereby obtaining RNA aptamer sequences with high binding affinity.

[0101] Based on the teachings of the present invention, those skilled in the art know that the RNA aptamer library used for screening can be a library from various sources, including but not limited to RNA aptamer libraries prepared by oneself, purchased commercially, or obtained through donation from others.

[0102] The solid support utilized in the method of the present invention may be any of various solid supports well known to those skilled in the art, including but not limited to magnetic beads, matrices, and the like. In preferred embodiments, the matrices include but are not limited to agarose gel matrices, cephalosporin beads, nitrocellulose, polyvinylidene fluoride membranes, octyl trehalose, and other carrier matrices.

[0103] The methods of the present invention are suitable for screening RNA aptamers that bind to various targets. In specific embodiments, the targets can be small molecules, including but not limited to steroids, dopamine, kanamycin, digoxin, antoxin, dinitroaniline, melamine, quinolones, and aflatoxins; the targets can also be macromolecules, including but not limited to polypeptides, proteins (such as enzymes and antibodies), complexes (proteins bound to RNA), high molecular weight polymers, and compounds.

[0104] When using a buffer gradient to elute the RNA aptamer bound to the target on the solid support, gradient elution can be achieved using a buffer with increasing volume or a buffer with increasing elution strength; preferably, gradient elution is achieved using a buffer with increasing volume.

[0105] In a preferred embodiment, the buffer with increased elution strength refers to a buffer with increased salt ion or chelating agent concentration to prevent RNA from folding to form a spatial structure.

[0106] To facilitate subsequent high-throughput sequencing, several background elutions can be performed before gradient elution until the number of RNA aptamer molecules in the eluate is no more than 1% of the high-throughput sequencing threshold. The volume of the background elution buffer should not be larger than the initial volume of the gradient elution buffer.

[0107] In a specific embodiment, the elution can be static elution (i.e., discontinuous elution, collecting the complete eluate at one time) or dynamic elution (i.e., continuous elution, continuously collecting a small amount of partial eluate), preferably static elution. Those skilled in the art are aware of the specific technical means for achieving the static elution and dynamic elution. For example, static elution can be achieved by soaking magnetic beads in a buffer solution; or dynamic elution can be achieved by flowing a buffer solution through a solid carrier, that is, in a manner similar to column chromatography. In a preferred embodiment, if static elution is adopted, the last background elution is carried out in a new container. The volume of the buffer solution for background elution may or may not be increased, preferably not increased. The buffer solution for background elution may be the same as or different from the buffer solution for gradient elution; preferably, the same.

[0108] In a specific embodiment, the buffer used for gradient elution contains magnesium ions, preferably 5 mM magnesium ions, a pH value below 8.5, preferably a pH value of 7-8, and a NaCl or KCl concentration between 75 mM and 200 mM.

[0109] The number of background washes can be determined based on the actual size of the library and the subsequent sequencing throughput. For example, if the number of molecules in the RNA aptamer library to be screened is 10 14 , while the NextSeq sequencing throughput is about 10 7 sequences / each eluate, the number of molecules needs to be reduced to less than 1% of the sequencing throughput (10 7 10 molecules sequenced 7 sequences, then an average of 1 sequence / single molecule, and <10 5 10 molecules sequenced 7 sequences, an average of 100 sequences / single molecule can be obtained, reducing the probability of obtaining a read of 1 sequence / single molecule due to random sampling), that is, 10 5＝14-7-2 Below; if each elution volume is 200μL, and the elution residual volume (including solid phase carrier) is about 2μL, the elution intensity is 200 / 2=10 2 , so at least 5 times 10 2 Background elution will cause the library to be eluted from 10 14 Reduced to 10 5 the following.

[0110] Similarly, after several gradient elutions, the number of RNA aptamer molecules contained in the eluate is suitable for sequencing, preferably reducing the theoretical minimum number of molecules in the library to 10 5 Next, complete elution is performed to completely elute the RNA aptamer bound to the target on the solid support.

[0111] Based on the molecular weight and length, those skilled in the art can understand the number of molecules in the library to be screened and thus predetermine the number of background elutions and the number of gradient elutions. In a specific embodiment, the number of background elutions and the number of gradient elutions can be increased by 1-2 times.

[0112] In the subsequent gradient elution, if static elution is used, as the elution volume increases, the system screening pressure also increases, and the elution liquid level is always higher than the previous elution liquid level, thereby reducing container tube wall contamination.

[0113] Compared to the prior art, the advantage of the present invention is that no RNA aptamer information in the library is lost. Therefore, the method of the present invention not only retains the eluent obtained by the above-mentioned background elution and gradient elution, but also performs complete elution after the gradient elution, thereby completely eluting the RNA aptamer bound to the target on the solid support. Accordingly, the buffer used for complete elution contains a reagent capable of releasing the RNA aptamer, including a reagent capable of destroying the binding of the target to the solid support, and / or a reagent capable of destroying the binding of the RNA aptamer to the target, and / or a reagent that directly destroys the target. Those skilled in the art know that they can independently decide or select a reagent capable of releasing the RNA aptamer according to the specific circumstances. For example, if the small molecule target is connected to a solid support coated with streptavidin via biotin, the buffer used for complete elution contains a reagent that separates the small molecule target from the solid support, such as DTT, and EDTA that separates the RNA aptamer from the small molecule target. For another example, if the target is a macromolecule, such as a protein, a reagent that cooperates with the protein, such as a protease, can be directly used to separate the RNA aptamer from the target. When using protease, it is important to note that the presence of the protease does not adversely affect the subsequent reverse transcriptase. For example, a protease inhibitor or a temperature-sensitive protease can be further used, so that the protease can be inactivated by increasing the temperature after complete elution, thereby not affecting the reverse transcriptase activity in subsequent steps.

[0114] After obtaining the eluate from the background elution, gradient elution, and complete elution, the RNA aptamers in the eluate can be concentrated and purified. Whether to concentrate and purify the RNA aptamers in the eluate can be determined by the technician based on specific needs. Without concentration and purification, the RNA aptamers in the eluate can be directly reverse transcribed using an instrument, but this results in a large solution volume and wastes reagents. Concentrating and purifying the RNA aptamers in the eluate can save reagents, but the concentration process can take several hours.

[0115] As described above, when amplifying and sequencing the RNA aptamers in the eluate, considering the problem of base imbalance, the inventors designed offset PCR to randomly insert a 0-6nt compensation sequence between the sequencing adapter and the cDNA constant region. However, after using the 0-6nt compensation sequence, the amplified DNA still has a small number of bases in an unbalanced distribution (for example, the 10th base of the 5'-end fixed sequence is missing an A, and bases 11-13 are also missing A, as shown in the 5'-end start sequence of V1 sequencing in Figure 2d (dark green and orange letters), and similarly, the 13-14th positions of the 3'-end fixed sequence are missing G, and the 8-12th positions of the middle pre-circular region are missing T). Therefore, a random sequence of approximately the average length of the library is added to the sequencing library, and fixed sequences missing from the library are used at unbalanced positions (e.g., at the 5'-end, random N is used for bases 1-7, G is used for base 8 to avoid six consecutive identical base fluorescence sequencing signals, and fixed base A is used for bases 9-13; at the 3'-end, random N is used for bases 1-7, and C, the complementary base of G, is used for base 13). In short, if there are still missing bases in the sequence after adding the offset, the custom sequence is used to supplement the missing bases. For positions where bases are not missing, the custom sequence can simply use random N.

[0116] Therefore, in the amplification and sequencing steps of the method of the present invention, a custom-designed PhiX was introduced during the mixing of multiple samples to further compensate for the unbalanced base distribution in the constant region.

[0117] In addition to not losing any RNA aptamer information in the library, the method of the present invention takes into account the binding potential of RNA aptamer candidate sequences when performing sequencing data analysis, thereby obtaining RNA aptamer sequences with high binding affinity. In a specific embodiment, the binding potential refers to the rapid increase in enrichment in each eluate, rather than simply considering the highest enrichment. In a preferred embodiment, the binding potential is judged according to one or more of the following information of the RNA aptamer: the abundance of the RNA aptamer in each eluate, the frequency of the RNA aptamer being detected separately in each eluate, and the RNA aptamer appearing in subsequent eluates better than in the initial eluate. In a preferred embodiment, the above information is fitted into a standard curve and the binding potential of the RNA aptamer is judged according to the area under the curve (AUC).

[0118] Based on the RNA aptamer screening method of the present invention, the present invention provides an apparatus for implementing the method of the present invention. Based on the teachings of the present invention, those skilled in the art will know how to construct an apparatus for implementing the method of the present invention. For example, the apparatus may include modules for performing each step of the method of the present invention.

[0119] Based on the teachings of the present invention, those skilled in the art will appreciate that the RNA aptamers screened using the methods of the present invention can be made into various products. For example, in specific embodiments, the RNA aptamers screened using the methods of the present invention can be made into biochips. In other embodiments, the RNA aptamers screened using the methods of the present invention can be made into pharmaceutical compositions.

[0120] Those skilled in the art will appreciate that if the RNA aptamers obtained by the inventive method screening have high binding affinity for specific recognition receptors on the cell surface, the RNA aptamers of the present invention can be attached to liposomes, thereby enabling specific delivery of drugs within the liposomes to designated cells. Therefore, the RNA aptamers obtained by the inventive method screening can be made into drug delivery vehicles. In a specific embodiment, the drug delivery vehicle is a liposome.

[0121] In other embodiments, the RNA aptamers screened using the method of the present invention can also be made into diagnostic reagents.

[0122] The beneficial effects of the present invention are as follows:

[0123] 1. The library has a low false positive rate (as low as 0%);

[0124] 2. The aptamers screened from the library have strong binding ability (K D 25 nM siR small molecule, 32 pM nsp12 large molecule);

[0125] 3. Short library preparation time, 1 round of screening (about 4 hours);

[0126] 4. Highly reproducible library preparation; and

[0127] 5. Library preparation can be further optimized for automated robotic arms (96 samples).

[0128] The present invention will be further described below in conjunction with specific examples. It should be understood that these examples are intended to illustrate the present invention only and are not intended to limit the scope of the invention. The experimental methods in the following examples, for which specific conditions are not specified, are generally based on conventional conditions or the conditions recommended by the manufacturer. Unless otherwise stated, percentages and parts are calculated by weight.

[0129] Example

[0130] Example 1. Preparation of RNA screening library source

[0131] 1.1. Random RNA Screening Library Source

[0132] 1.1.1 Synthesis of single-stranded DNA template

[0133] A 103 nt ssDNA template library was custom-made from a primer reagent company. The template (5'-3' end) consisted of a primer A binding region (19 nt) [Famulok, M. Molecular Recognition of Amino Acids by RNA-Aptamers: An L-Citrulline Binding RNA Motif and Its Evolution into an L-Arginine Binder. J Am Chem Soc 116, 1698-1706, doi: 10.1021 / ja00084a010 (2002)], a left arm random region (26 nt), and a pre-circular fixed region (12 nt) [Davis, JH & Szostak, JW Isolation of high-affinity GTP aptamers from partially structured RNA libraries. Proc Natl Acad Sci USA 99, 11616-11621, doi: 10.1073 / pnas.182095699 (2002)], a right arm random region (26 nt), and a primer B binding region (20 nt) [Famulok, M. Molecular Recognition of Amino Acids by RNA-Aptamers: An L-Citrulline Binding RNA Motif and Its Evolution into an L-Arginine Binder. J Am Chem Soc 116, 1698-1706, doi: 10.1021 / ja00084a010 (2002)] (see Figure 2a). During the synthesis of the random region, artificial premixed nucleotide substrates were used, with an A:C:G:T ratio of 3:3:2:2. The entire reaction set was commercially synthesized on a 1 μmol scale.

[0134] Purification of single-stranded DNA template

[0135] The ssDNA template library (~200 μg, 0.5 mL) was purified using a 10% polyacrylamide gel (20 cm x 40 cm) at 20W for 1.5 h. Synthesis byproducts were separated by electrophoresis under UV light (254 nm for DNA imaging and 365 nm for RNA imaging). The main product was labeled, the gel was cut, and the DNA was dissolved in 5 mL of 0.3 M NaOAc (pH 5.5) with rotation (550 rpm) overnight. The DNA was precipitated overnight with 3 volumes of EtOH and centrifuged at 4°C (14,000 g) for 30 minutes. The pellet was then rinsed with 2 mL of 70% EtOH and centrifuged at 4°C (14,000 g) for 10 minutes. The rinse was repeated with 0.5 mL of 70% EtOH. Finally, the DNA pellet was dried at room temperature and dissolved in TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0).

[0136] 1.1.3. Amplification of double-stranded DNA template

[0137] 0.16 μM purified ssDNA, 5 μM primer A (see Table 1), 5 μM primer B (see Table 1), 1x Taq buffer (10 mM Tris-HCl, pH 8.4, 50 mM KCl, 0.1% (v / v) Triton X-100), 500 μM dNTPs, 6 mM MgCl2, and 0.1 U / μL Taq DNA polymerase were used in a total reaction volume of 30 mL. The PCR reaction was initially heated to 94°C for 3 minutes, followed by 6 cycles (each cycle consisting of denaturation at 94°C for 1 minute, annealing at 52°C for 1 minute, and extension at 72°C for 3 minutes), followed by a final extension step (72°C for 20 minutes) and cooling to 4°C.

[0138] 1.1.4. Purification of double-stranded DNA template

[0139] An equal volume of P / C / I reagent was added, vortexed for 30 seconds, and centrifuged at 14,000 g for 20 minutes at room temperature. The supernatant aqueous phase was transferred to a new 50 mL centrifuge tube. An equal volume of chloroform was then added, vortexed, centrifuged, and the aqueous phase was transferred. The chloroform extraction process was repeated once more. Finally, dsDNA was precipitated in 70% EtOH, 0.3 M NaOAc, and the pellet was washed with ethanol, dried, and dissolved in 200 μL of TE buffer.

[0140] In vitro RNA transcription

[0141] 534 nM purified dsDNA was added to 1X transcription buffer (40 mM Tris-HCl pH 8.1, 1 mM spermidine, 22 mM MgCl2, 0.01% Triton X-100) with 10 mM DTT, 5% (v / v) DMSO, 1 U / mL pyrophosphatase (optional), 4 mM ATP / CTP / GTP / UTP, 40 μg / mL acetylated BSA (Sigma-Aldrich) (optional), and 0.7 μM T7 polymerase (Thermo Fisher Scientific) in a total reaction volume of 10 mL. For in vitro transcription of 2'-hydroxyfluorinated RNA, the CTP and UTP substrates were replaced with equal concentrations of 2'-F-CTP (Jena Bioscience) and 2'-F-UTP (Jena Bioscience), and the T7 polymerase was replaced with equal concentrations of a mutant T7 polymerase (Y639F, prepared in-house). All other components remained unchanged. The in vitro transcription reaction was incubated at 37°C for 4 hours. Subsequently, 50 U / mL DNase I was added, and the reaction was incubated at 37°C for an additional hour. The desired RNA was obtained by P / C / I purification and two chloroform extractions, followed by isopropanol precipitation at -20°C for 1 hour and two 75% ethanol washes. The RNA was then dissolved in dHO and stored at -20°C or -80°C for long-term storage.

[0142] 1.2. Preparation of Directed Random RNA Library Source

[0143] The preparation process of the directional random RNA library source is similar to that of the random RNA library source except for the synthesis of ssDNA template and PCR amplification and purification of dsDNA.

[0144] 1.2.1. Synthesis of single-stranded DNA template

[0145] When synthesizing the ssDNA template library, based on the known ancestral sequence information (103 nt, see Table 1), during the synthesis process, the corresponding random regions used artificial premixed nucleotide substrates, whose original bases and the other three non-original bases were in a ratio of 85:5:5:5, and were also commercially synthesized at a scale of 1 μmol.

[0146] 1.2.2. Amplification of double-stranded DNA template

[0147] For dsDNA amplification, PCR amplification was performed using 50 nM ssDNA as the template in 1X Taq buffer with 5 μM Primer A, 5 μM Primer B, 500 μM dNTPs, 1.5 mM MgCl2, and 0.05 U / μL Taq DNA polymerase in a total volume of 1 mL. The PCR process was the same as for random RNA library preparation.

[0148] 1.2.3. Amplification of double-stranded DNA template

[0149] PCR products were purified using the QIAquick PCR Purification Kit (QIAGEN). 400 nM of purified dsDNA was used for in vitro transcription in a total volume of 2 mL. RNA was purified by polyacrylamide gel electrophoresis (PAGE), dissolved in dH2O, and stored under the same storage conditions as described above.

[0150] Example 2. Screening and sequencing of RNA aptamers

[0151] RNA higher-order structural folding

[0152] Random or directed random library-derived RNA, yeast-tRNA (Invitrogen) and competitor RNA (see Table 1) were incubated at 75°C for 5 minutes, then slowly cooled to 4°C at a rate of 0.1°C / s and placed on ice.

[0153] 2.2.a. Screening RNAs that bind to small molecules (e.g., biotinylated silica rhodamine)

[0154] 2.2.1.a. Pre-equilibrated magnetic beads

[0155] Hydrophilic streptavidin magnetic beads (New England Biolabs) were enriched using a 6-tube magnetic separation rack (New England Biolabs), washed five times with 1X ASB buffer (20 mM HEPES pH 7.4, 125 mM KCl, 5 mM MgCl2) with 4 times the volume of magnetic beads, and then resuspended in 1X ASB buffer with 0.5 magnetic beads.

[0156] 2.2.2.a. Blocking Magnetic Bead Background: 5 μM biotin-linked silica rhodamine was incubated with 25% (v / v) concentrated magnetic beads (2.1.a) in 100 μL of 1X ASB buffer: Group A, no additional reagents ("+None" RLA); Group B, 0.15 μg / μL folded yeast tRNA ("+tRNA" RLB); or Group C, 4 μM folded competitor RNA 1 (see Table 1), ("+cRNA" RLC). After thorough mixing, incubate at 25°C for 30 minutes at 1000 rpm.

[0157] 2.2.3.a. Equilibration of Blocked Magnetic Beads

[0158] Wash five times with 200 μL of 1X ASB buffer. Gently mix the beads each time, let them stand at room temperature for 30 seconds, then place them on a magnetic rack, remove the liquid, and quickly add 1X ASB buffer to prevent the beads from drying out.

[0159] 2.2.4.a. Binding to RNA

[0160] Prepare 4 μM of random library RNA in 100 μL of 1X ASB buffer. After washing the blocked magnetic beads, resuspend them in the RNA solution, mix thoroughly, and incubate at 25°C, 1000 rpm for 1 hour.

[0161] 2.2.5.a. Gradient Screening and Washing RNA

[0162] Collect the beads using a magnetic rack, remove the supernatant, and then wash the RNA-bound beads four times with 200 μL of 1X ASB buffer. Collect each wash separately. After each resuspended beads, let them rest for 30 seconds before placing them on the magnetic rack. Resuspend them again in 200 μL of 1X ASB buffer and transfer them to a new 1.5 mL centrifuge tube. Collect the beads on the magnetic rack, collect the fifth wash, and then wash them five more times with 250 μL, 300 μL, 350 μL, 400 μL, and 450 μL of 1X ASB buffer, again collecting each wash separately, for a total of 10 washes. Finally, perform a complete elution by incubating the beads with 200 μL of 50 mM DTT at 25°C for 20 minutes at 650 rpm. Collect this eluate and combine it with the second eluate to form the 11th wash. The second eluate was incubated with 100 μL of 50 mM DTT and 5 mM EDTA at 25°C for 5 min at 650 rpm.

[0163] 2.2.6.a. Concentration and purification of RNA

[0164] Add 3 volumes of chilled EtOH, 0.1 volumes of 3M NaOAc, and 1 μL of glycogen (Thermo Fisher Scientific). Precipitate the 10 washes and the combined eluate from step 2.5.a at -20°C for 2 hours or overnight. Centrifuge the precipitated RNA (4°C, >20,000g, 1 hour), wash, and dissolve in 10 μL of dH2O. [Optional step: The reaction volume in step 2.4.a. RNA binding can be reduced to 20 μL, and the addition of 5 mM EDTA in the second elution step in step 2.5.a. can be omitted. At this point, the 10 washes and the combined eluate can be added directly to the reverse transcription reaction without the RNA precipitation step in step 2.6.a.]

[0165] 2.2.b. Screening for RNAs that bind to macromolecules (e.g., His-tagged SARS-CoV-2 replicase)

[0166] 2.2.1.b. Pre-equilibrated magnetic beads

[0167] HisPur was separated using a 6-tube magnetic separation rack (New England Biolabs). TM Ni-NTA magnetic beads (Thermo Fisher Scientific) were enriched, washed and equilibrated five times with 1X ERB buffer (100 mM NaCl, 20 mM Na-HEPES pH 7.5, 5% (v / v) glycerol, 10 mM MgCl2 and 0.5 mM β-mercaptoethanol (optional addition)) with 4 times the volume of magnetic beads, and then resuspended in 1X ERB buffer with 0.3 times the volume of magnetic beads.

[0168] 2.2.2.b. Blocking magnetic bead background

[0169] Add 50% (v / v) concentrated equilibrated magnetic beads (2.1.a) to 30 μL of 1X ERB buffer: No additional reagents are required for Group A ("+None" or NLA); 0.4 μg / μL of folded yeast tRNA is added for Group B ("+tRNA" or NLB); or 10 μM of folded competitor RNA 2 (see Table 1) is added for Group C ("+cRNA" or NLC). Mix the reaction thoroughly and incubate at 25°C for 2 minutes. Then, add 50 μL of 30 μM nsp12 in 1X ERB buffer, mix thoroughly and gently, and incubate at 25°C for 10 minutes, flicking the tube to mix.

[0170] 2.2.3.b. Equilibration of Blocked Magnetic Beads

[0171] Wash five times with 200 μL of 1X ERB buffer. Gently mix the beads after each wash. Let them stand at room temperature for 30 seconds, then place them on a magnetic rack, remove the liquid, and quickly add 1X ERB buffer to prevent the beads from drying out.

[0172] 2.2.4.b. Binding to RNA

[0173] Prepare 4 μM of random library RNA in 100 μL of 1X ERB buffer. After washing the blocked magnetic beads, resuspend them in the RNA solution, mix thoroughly and gently, and incubate at 25°C for 10 minutes, flicking the beads to mix. Then, incubate at 37°C for 5 minutes, and finally at 25°C for 2 minutes.

[0174] 2.2.5.b. Gradient Screening and Washing RNA

[0175] The beads were collected using a magnetic rack, and the supernatant was removed. RNA-bound beads were then washed four times with 200 μL of 1X ERB buffer, collecting each wash separately. After each resuspended bead, the beads were allowed to rest for 30 seconds before being placed on the magnetic rack. The beads were then resuspended in 200 μL of 1X ERB buffer and transferred to a new 1.5 mL centrifuge tube. The beads were then concentrated on the magnetic rack, and the fifth wash was collected. Washes were then repeated five times with 250 μL, 300 μL, 350 μL, 400 μL, and 450 μL of 1X ASB buffer, again collecting each wash separately, for a total of 10 washes. Finally, a complete elution was performed, first with 400 μL of 1X ERB buffer containing 0.1 U / μL proteinase K (New England Biolabs) and 2 mM CaCl₂, incubated at 37°C for 45 minutes, with finger flicking to mix. This eluate was collected and combined with the second eluate to form the 11th wash. The second eluate was incubated with 100 μL of 1X ERB buffer at room temperature for 1 minute and then recovered using a magnetic rack. The combined eluate was made up to 500 μL and subjected to two P / C / I extractions and purifications, and the supernatant was recovered.

[0176] 2.2.6.b Concentration and purification of RNA

[0177] Add 3 volumes of chilled EtOH, 0.1 volumes of 3M NaOAc, and 1 μL of glycogen (Thermo Fisher Scientific). Precipitate the 10 washes and the combined eluate from step 2.5.a at -20°C for 2 hours or overnight. Centrifuge the precipitated RNA (4°C, >20,000g, 1 hour), wash, and dissolve in 10 μL of dH2O. [Optional: The reaction volume in step 2.4.b RNA binding can be reduced to 20 μL. In step 2.5.6 Complete Elution, replace proteinase K with 0.015 U / μL of thermosensitive proteinase K (New England Biolabs). Incubate at 25°C for 1 hour, gently mixing with a finger. Then, incubate the reaction at 55°C for 10 minutes to inactivate the thermosensitive proteinase K. At this point, the 10 washes and the combined eluate can be added directly to the reverse transcription reaction without the RNA precipitation step in step 2.6.b.]

[0178] Reverse transcription of RNA

[0179] For reverse transcription in a final volume of 20 μL, 2.6 μg of RNA was added to 0.5 μM Primer B, 0.5 mM dNTPs, and dHO and reacted at 65°C for 5 minutes. After the reaction, the system was immediately cooled on ice for 2 minutes. Then, 1X SSIV buffer (Thermo Fisher Scientific), 5 mM DTT, and 10 U / μL SuperScript IV reverse transcriptase (Thermo Fisher Scientific) were added to the reaction, and the mixture was incubated at 53°C for 1 hour.

[0180] 2.4. Offset PCR dsDNA Compensation

[0181] To incorporate the compensatory sequence into the library, 10 μL of the completed reverse transcription reaction was further PCR amplified with 1X Taq buffer, 0.2 mM dNTPs, 3 μM offset selex frw primer mix v1 (or v2), 3 μM offset selex frw primer mix v1 (or v2) (see Figure 2d and Table 1), 2 mM MgCl2, and 0.05 U / μL Taq DNA polymerase in a total volume of 50 μL. The PCR reaction was first heated to 94°C (3 minutes), followed by 11 cycles (each cycle consisting of 94°C denaturation for 1 minute, 52.5°C annealing for 1 minute, and 72°C extension for 2 minutes), followed by a final extension step (72°C for 5 minutes) and then cooled to 4°C.

[0182] 2.5. Offset PCR dsDNA Purification

[0183] Ampure XP magnetic beads (Beckman Coulter) were pre-equilibrated at room temperature for at least 30 minutes. 1.2 times the reaction volume of magnetic beads were added to the PCR reaction and pipetted up and down 40 times to mix thoroughly for purification. The beads were allowed to stand at room temperature for 10 minutes and then placed on a SMARTer-Seq PCR magnetic rack (Takara Bio). After the beads were fully enriched, they were removed and washed twice with 180 μL 80% EtOH. The beads were dried at room temperature for approximately 5 minutes, and 30 μL dH2O was added. The beads were pipetted up and down to mix thoroughly. The beads were allowed to stand at room temperature for 5 minutes and then placed on a magnetic rack. The dsDNA solution was collected and the approximate concentration was measured using a Nanodrop nucleic acid concentrator (Thermo Fisher Scientific).

[0184] Illumina PCR dsDNA labeling

[0185] Sequencing primers and tag sequences were further added to the dsDNA by PCR using ~4.5 nM offset-PCR dsDNA template, 500 nM sequencing universal primer (New England Biolabs), 500 nM sequencing index primer (New England Biolabs), 200 nM dNTPs, 1× Q5 reaction buffer (New England Biolabs), 0.02 U / μL hot start Q5 high-fidelity DNA polymerase (New England Biolabs), and dH2O in a total volume of 50 μL. The PCR reaction was initially heated to 98°C (40 s) and then subjected to six cycles (each cycle consisting of denaturation at 98°C for 10 s, annealing at 68.5°C for 20 s, and extension at 72°C for 30 s), followed by a final extension step (72°C for 2 min) and cooling to 4°C.

[0186] Illumina PCR dsDNA purification

[0187] As in step 5, dissolve dsDNA with 15 μL dH2O and store at -20°C.

[0188] 2.8. Sequencing library quality control

[0189] A 1 μL sample was used to measure the precise concentration of the sample using a Qubit Fluorometer (Invitrogen) to confirm that the sample concentration was greater than 2 ng / μL. Another 1 μL sample (diluted to 1-2 ng / μL) was then used for high-precision electrophoresis analysis and quality control on a Bioanalyzer (Agilent) to confirm that the signal peak was around 225 bp.

[0190] 2.9. Multiple Sample Sequencing

[0191] No more than 47 quality control samples were mixed at the same concentration, and 5% selexPhiX_v1 (using offset_selex_primer v1 in step 5) or selexPhiX_v2 (using offset_selex_primer v2 in step 5) was added. The samples were diluted to a final concentration of 20 nM, diluted, and denatured with NaOH. Sequencing was performed using the NextSeq 500 single-end (SE) high-throughput 75 bp sequencer at a sequencing density of 1.8 pM. The 10 bp reagent used for sequence tagging was used for sequencing the sequences themselves, resulting in a total sequence output of 86 bp, approximately 320-400 million reads.

[0192] Example 3. Data modeling analysis and statistics

[0193] Data cleaning

[0194] According to the primer index sequence (6nt) used for each sample, the original sequencing data is decoded and classified into the corresponding sample sequence. In the process of corresponding index sequence, zero mismatch is taken as the standard, and at the same time, low phred quality sequences are filtered. Then, the compensation sequence (7 types, 0-6nt) at the 5'-end of the sequence is cut off, and the balanced distribution of the compensation sequence is statistically analyzed. The sequence after cutting is further removed from the primer B corresponding sequence, the 67nt source sequence is retained, and the source sequence is reverse complemented and adjusted back to the DNA sequence consistent with the original RNA sequence. In the process of cutting the sequence, background data with no compensation sequence, no primer B sequence, more than 25 consecutive identical bases, and a length of less than 65nt after trimming are cleaned up.

[0195] 3.2. Data Merging

[0196] Create a data frame (12 columns by n rows). Column 1 contains the sequence itself, and columns 2-12 contain the 10 wash groups and 1 combined elution group (groups 1-11, g1-11, respectively) grouped in 2.2.5. Each row represents independent and exclusive sequence statistics for a library. For the cleaned data from 3.1, calculate the abundance of each sequence within groups 1-11 and record it in the data frame. Next, remove from the merged data frame any parent sequences with an edit distance of more than 4 compared to the theoretical pre-circular sequence in the fixed region of the pre-circular region. Also remove any parent sequences containing an unknown "N" in the random regions of the left and right arms. Finally, compress and store the merged database of normalized sequences.

[0197] Data Conversion

[0198] In the merged database, for sequences with an abundance of 0 in group 1, the abundance is replaced with the initial non-zero value of 0.5. Then, a fold change database (11 columns * m rows) is created, with the first column being the sequence itself, the second column being the group 2 change ratio (f2), which is the abundance of the sequence in group 2 divided by the corresponding abundance of the sequence in group 1, and the third column being the group 3 change ratio (f3), which is the abundance of the sequence in group 3 divided by the corresponding abundance of the sequence in group 1. For ratios of 0, the values ​​are replaced with 0.1. Finally, the log2 logarithm is taken and the fold change database is saved.

[0199] 3.4. Sorting Modeling

[0200] In the fold-change database, for each set of change ratios, we sorted them from high to low, and selected the sequence at the 1% (scale percentile) as the scale-passing sequence. Then, based on the initial gamma trendline (Changshu c* interval ratio gamma - 0.0000001), with a default gamma value of 1, we generated 10 ratios: 0.1, 0.2, 0.3, …, 0.9, and 1. We scaled the ratios of each set of scale-passing sequences to the corresponding ratios as a weighting process. For example, if the original ratio of the first set of scale-passing sequences was 5, then the ratios of all the first set of sequences were divided by 50. If the original ratio of the second set of scale-passing sequences was 7, then the ratios of all the second set of sequences were divided by 35, and so on. Finally, for each sequence in the 10 sets of change ratios, we calculated 10 corresponding gamma change rates (gf). Using 1-10 as the horizontal axis and the corresponding gamma change rates as the vertical axis, we calculated the area under the curve (auc). The binding ability of the sequence is predicted based on its AUC value. The larger the value, the stronger the potential binding ability, and vice versa.

[0201] 3.5. Model Fine-tuning

[0202] In the model, the hyperparameters gamma and scale quantile can be adjusted based on the distribution and ratio of the raw abundance of a few potential strong binding sequences across groups, as well as the enrichment routes. They can also be further optimized based on the Pearson correlation coefficient of subsequences of strong binding sequences. A gamma ≥ 1 is recommended for small molecules, and gamma ≤ 1 for large molecules. A scale quantile of 1% is recommended. For subsequence analysis, several strong binding sequences are first selected from the merged data frame. Each sequence is split into a left-arm random region, a pre-loop region, and a right-wing random region. The primer A residue sequence is further removed from the left-arm random region. A sliding window of size n (6-10) with a step size of 1 is applied to each region to calculate the abundance of subsequence features of the high-abundance sequences in each group. The trend of the enrichment correlation coefficient is used as a reference for hyperparameter adjustment. Furthermore, after measuring the binding strength of a small number of candidate sequences, the normalized discounted cumulative gain (NDCG) method can be used to further optimize the ranking-related hyperparameters gamma and scale quantile.

[0203] Example 4. Screening and Validation

[0204] 4.1. Determination of the Dissociation Constant of the Interaction between RNA Aptamer and Silirhodamine

[0205] The dissociation constant (KD) of the RNA aptamer with silica rhodamine was determined by JASCO fluorescence intensity at various RNA concentrations. Briefly, the RNA ligand was folded according to step 2.1. The RNA was then mixed with 50 nM SiR-PEG2-NH2 probe in 1X ASB buffer in a fluorimeter cuvette at 25°C. Fluorescence intensity was recorded as the concentration of the RNA increased. The excitation and emission wavelengths were set to 647 nm and 662 nm, respectively, and the slit widths for excitation and emission were set to ±5 nm. The dissociation constant was determined by simulating the binding curve using the Hill equation.

[0206] 4.2. RNA Aptamer-Activated Silica Rhodamine Fluorescence Measurement and Live Cell Imaging

[0207] The RNA ligand (5 μM) was folded according to step 2.1. The RNA solution was then dissolved in 1x ASB buffer, and 5 nM SiR-PEG2-NH2 probe was added. The cells were incubated at room temperature for 10 minutes. Fluorescence was measured using a JASCO spectrophotometer (λex = 647 nm; λem = 662 nm (±5 nm slit width)). For live-cell imaging, human embryonic kidney 293 (HEK293T) cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM, high glucose, without phenol red) (Gibco) supplemented with 10% fetal bovine serum (FBS) (Gibco), 100 U / mL penicillin (Thermo Fisher Scientific), and 100 μg / mL streptomycin (Thermo Fisher Scientific). A portion of the activated cells was seeded in 300 μL of culture medium and transferred to 8-well glass chambers coated with poly-D-lysine for overnight growth. Cells were then transfected with the appropriate amount of expression plasmid using FuGeneHD transfection reagent (Promega) according to standard protocols. After 48 hours, the culture medium was exchanged with Leibowitz (L15) medium containing 200 nM SiR-PEG-NH2. Cells were imaged and photographed at 37°C, and visualization was adjusted accordingly.

[0208] 4.3. Determination of the dissociation constant of the interaction between RNA aptamers and SARS-CoV-2 replicase

[0209] Based on the principle of biofilm interference, The dissociation constant was measured using the R8 system (Sartorius). Ni-NTA (NTA) biosensors (Sartorius) were equilibrated for 5 minutes in 1X ERBL buffer (20 mM Tris-HCl pH 7.4, 100 mM KCl, 5% (v / v) glycerol, 10 mM Mg(OAc)2, 1 mM TCEP, 0.02% TWEEN20 (Carl Roth)) before dissociation constant measurement. RNA was serially diluted 2-fold in 1X ERBL buffer from the indicated concentration in each well, while wells containing 1X ERBL buffer without RNA served as blank controls. Simultaneously, 20 ng / μL of His10-nsp12 was used in the protein loading step. The assay consisted of a 60-second baseline-1 step, a 180-240-second protein loading step, a 60-second baseline-2 step, a 900-1800-second association step, and a 600-3600-second dissociation step. Data were analyzed using Octet data analysis software. In brief, data were preprocessed by reference control subtraction, Y-axis alignment based on baseline mean, correction between dissociation steps, and Savitzky-Golay filtering. A 1:1 binding model was used. Dissociation constants were then calculated using the appropriate fitting method (local or global). Ni-NTA biosensors are reusable. In brief, the biosensors were washed repeatedly for three cycles, consisting of a 10 mM glycine (pH 1.7) wash (10 sec) and a 1X ERB buffer neutralization (10 sec), followed by a 10 mM NiCl2 regeneration (70 sec) and a 1X ERB buffer wash (60 sec), all performed with shaking at 1000 rpm.

[0210] 4.4. RNA aptamer 3'-end blocking modification

[0211] 3.77 μM RNA aptamer was added to a 200 μL reaction solution containing 10 mM NaOAc pH 4.5, 50 mM freshly prepared NaIO4, and dH2O and incubated at room temperature for 2 minutes. The oxidation reaction was then quenched by adding 10% (v / v) ethylene glycol, mixing repeatedly, and standing at room temperature for 5 minutes. The quenched reaction was further supplemented with 222 mM Tris-HCl pH 8.9, 0.15 M NaOAc pH 5.5, 2 μL glycogen (Thermo Fisher Scientific), and 50% (v / v) isopropanol. The reaction mixture was incubated at room temperature for an additional 30 minutes. Finally, the RNA was precipitated by centrifugation (16,000 g, 20 minutes, 4°C) and washed twice with 75% EtOH. The RNA was dissolved in dH2O and stored at -20°C or -80°C for long-term storage.

[0212] The sequencing library-related sequences, RNA aptamer sequences, and control group sequences of the present invention are shown in Table 1 and Table 2, respectively.

[0213] Among them, for siR small molecules, RLB7 (KD 250nM), RLB15 (KD 194nM), RLB3 (KD 208nM), RLB4 (KD 195nM), RLB8 (KD 700nM), RLB12 (KD 370nM), RLB13 (KD 461nM), and seqB (also RLB108, KD 25nM) all showed excellent affinity;

[0214] For nsp12 protein, NLB113, NLB41, NLB30, NLB79, NLB34, NLB69, NLB32, NLB2, NLB58, and NLB5 showed excellent affinity.

[0215] discuss

[0216] Since the 1990s, technologies for discovering high-affinity aptamers have been developed and have achieved remarkable success. However, the entire evolutionary selection process is considered a "black box" operation, typically requiring weeks or even months. While high-throughput sequencing tools enable visualization of each round of sequence selection, they do not address the high false-positive rate of selected aptamers. With the development of sophisticated instrumentation and algorithms, the number of iterations in the screening process has been reduced, resulting in aptamers with higher affinity and specificity. One promising "partitioning" method uses capillary electrophoresis for rapid screening of DNA aptamers. However, in addition to requiring complex instrumentation and fabrication techniques, a limitation is that when an aptamer binds to a target with a smaller molecular weight than itself, it does not generate sufficient mobility shift signals to distinguish binding characteristics. Similarly, optimizing the selection conditions (such as bead aggregation, microbubbles, and RNA stability) of microfluidic chip separation systems for different binding targets is not easy. In addition, computational prediction of aptamer binding mainly utilizes subsequence and substructure information of RNA sequences, but this type of data-driven analysis is highly dependent on the data corresponding to manual selection screening rounds and the quality of traditional screening experiments.

[0217] The RNA aptamer screening method developed by the present invention for small and large molecules only takes a few hours. Direct single-round RNA screening does not require demanding instrumentation, and efficient deep sequencing library construction is possible. The method of the present invention can be used for end-to-end analysis and is extremely easy to use. In the method of the present invention, the characteristics of SGRELI maximize the useful information generated during the selection process. High-affinity RNA aptamers can be observed multiple times and have a gradient ranking trend, resulting in a low false positive rate for predicted binding aptamers.

[0218] According to the above examples, it can be seen that the SiR RNA aptamers obtained by the method of the present invention have better KD and fluorescence activation ability. Compared with the best aptamer SIRA reported so far, they have increased specificity and reduced the background of RNA live cell images. In addition, the sequence length and composition can be further optimized based on structural interaction information. The nsp12 RNA aptamer with pM KD obtained by the method of the present invention provides an application prospect for inhibiting SARS-CoV-2 polymerase replication. Further 3'-end blocking modification of the aptamer is a necessary condition for completely inhibiting polymerase extension. Compared with remdesivir, the aptamer obtained by the present invention achieves the same inhibitory effect at the same RdRp polymerase concentration, requiring only one thousandth of the working concentration of remdesivir. RNA aptamers with 3'-end structures entering and occupying the catalytic center of the replicase complex may be the key to inhibiting viral replication. At the same time, the present invention is applied to screening chemically modified RNA aptamers, and the resulting aptamers efficiently inhibit HIV-1 reverse transcriptase replicase, further expanding the scope of application of the screening of the present invention. Further optimization of the method of the present invention can use machine learning and feature engineering (such as substructure, subsequence) to predict binding affinity, and can also use automated robots for high-throughput screening.

[0219] In summary, the present invention emphasizes a method with SGRELI characteristics for rapid screening of RNA aptamers and provides a theoretical basis for the development of functional RNA aptamers that activate chemical dyes and inhibit SARS-CoV-2 polymerase and HIV-1 reverse transcriptase.

[0220] All documents mentioned in this application are incorporated herein by reference, just as if each document were incorporated herein by reference individually. It should also be understood that after reading the above teachings of the present invention, those skilled in the art may make various changes or modifications to the present invention, and that such equivalents also fall within the scope of the claims appended hereto.

[0221] Table 1. Sequences of sequencing libraries

[0222] Table 2. RNA aptamer sequences of the present invention and control group sequences (fC and fU in the sequence represent the nucleotides, i.e., C and U are fluorinated, such as 2'-F-CTP and 2'-F-UTP)

Claims

1. A method for screening RNA aptamers, comprising the following steps: 1) Providing an RNA aptamer library to be screened; 2) incubating the library from step 1) with a solid support bound to the target, thereby promoting the RNA aptamers in the library to fully bind to the target; 3) eluting the RNA aptamer bound to the target on the solid support in step 2) using a buffer gradient, and collecting the eluate from each elution; 4) Completely eluting the RNA aptamers still retained on the solid support after step 3), and collecting the eluate as the last set of eluate; 5) optionally concentrating and purifying the RNA aptamers in the eluate obtained in steps 3) and 4); 6) Reverse transcribing the RNA aptamer obtained in step 5) to obtain cDNA; 7) amplifying and performing high-throughput sequencing on the cDNA obtained in step 6) to obtain sequencing data; 8) Analyze the sequencing data obtained in step 7) and sort the candidate RNA aptamer sequences from high to low according to their binding potential, thereby obtaining RNA aptamer sequences with high affinity.

2. The method according to claim 1, wherein Providing the RNA aptamer library to be screened includes preparing it by oneself, purchasing it commercially, or obtaining it through donation from others.

3. The method according to claim 1, wherein In step 2), after the RNA aptamers in the RNA aptamer library bind to the target, the solid support can be sealed to control and reduce non-specific background binding.

4. The method according to claim 3, wherein: The blocking is blocking the solid support with non-target specific random RNA; or blocking the solid support with target specific RNA.

5. The method according to claim 1, wherein In step 2), the solid carrier includes but is not limited to: magnetic beads and matrix.

6. The method according to claim 5, wherein The matrix includes but is not limited to: agarose gel matrix, cephalosporin beads, nitrocellulose, polyvinylidene fluoride membrane, octyl trehalose and other carrier matrices.

7. The method according to claim 1, wherein In step 2), the target is a small molecule, including but not limited to: steroids, dopamine, kanamycin, digoxin, antoxin, dinitroaniline, melamine, quinolone, aflatoxin; a macromolecule, including but not limited to: polypeptides, proteins (such as enzymes and antibodies, etc.) and complexes (proteins bound to RNA), high molecular polymers and compounds, etc.

8. The method according to claim 1, wherein In step 3), the gradient elution is performed using a buffer with an increasing volume, or a buffer with an increasing elution strength; preferably, the elution is performed using a buffer with an increasing volume.

9. The method according to claim 8, wherein The buffer with increased elution strength refers to a buffer that increases the concentration of salt ions or chelating agents to prevent RNA from folding to form a spatial structure.

10. The method according to claim 8, wherein Before gradient elution, several background elutions are performed until the number of RNA aptamer molecules contained in the eluate is no more than 1% of the high-throughput sequencing threshold.

11. The method according to claim 10, wherein The volume of buffer used for background elution should not be larger than the initial volume of buffer used for gradient elution.

12. The method according to claim 1, wherein The elution can be static elution (discontinuous elution, collecting the complete eluate at one time) or dynamic elution (continuous elution, continuously collecting a small amount of partial eluate), preferably static elution.

13. The method according to claim 12, wherein: If static elution is used, the final background elution is performed in a new container.

14. The method according to claim 10, wherein The volume of the background elution buffer may or may not be increased, preferably not increased.

15. The method according to claim 10, wherein The buffer for background elution can be the same as or different from the buffer for gradient elution; preferably, they are the same.

16. The method according to claim 1, wherein The buffer used for gradient elution contains magnesium ions, preferably 5 mM magnesium ions, a pH value below 8.5, preferably a pH value of 7-8, and a NaCl or KCl concentration between 75 mM and 200 mM.

17. The method according to claim 8, wherein After several gradient elutions, the number of RNA aptamer molecules contained in the eluate is suitable for sequencing, preferably the theoretical minimum number of molecules in the library is reduced to 10 5 Next, complete elution is performed in step 4) to completely elute the RNA aptamer bound to the target on the solid support.

18. The method according to claim 1, wherein The buffer used for complete elution contains reagents capable of releasing RNA aptamers, including reagents capable of destroying the binding of the target to the solid support, and / or reagents capable of destroying the binding of the RNA aptamer to the target, and / or reagents that directly destroy the target.

19. The method according to claim 1, wherein In step 7), a 0-6 nt compensation sequence is randomly inserted between the sequencing adapter and the cDNA constant region.

20. The method according to claim 19, wherein In step 7), during the mixing of multiple samples, a custom-designed PhiX was introduced to further compensate for the unbalanced base distribution in the constant region.

21. The method according to claim 1, wherein In step 8), the binding potential refers to the fastest increase in the enrichment level in each eluate, rather than simply considering the highest enrichment level.

22. The method according to claim 21, wherein The binding potential is determined based on one or more of the following information about the RNA aptamer: the abundance of the RNA aptamer in each eluate, the frequency with which the RNA aptamer is detected individually in each eluate, and whether the RNA aptamer appears in subsequent eluates more frequently than in initial eluates.

23. The method according to claim 22, wherein The above information was integrated into a standard curve and the binding potential of the RNA aptamer was evaluated according to the area under the curve (AUC).

24. The method according to any one of claims 1 to 23, wherein The RNA aptamer comprises a chemically modified sequence; preferably a fluorine-modified sequence.

25. An RNA aptamer, which is obtained by screening using the method according to any one of claims 1 to 24.

26. The RNA aptamer according to claim 25, wherein The RNA aptamer includes an RNA aptamer with a known sequence but random modifications on different bases (such as A, U, G, C).

27. The RNA aptamer according to claim 25, wherein The RNA aptamers do not include conventional RNA aptamers with known sequences and no additional modifications.

28. The RNA aptamer according to claim 25, wherein The RNA aptamer comprises a chemically modified sequence; preferably a fluorine-modified sequence.

29. An apparatus for carrying out the method of any one of claims 1 to 24.

30. The apparatus of claim 29, wherein The device includes the following modules: 1) a preparation module, wherein the module prepares an RNA aptamer library to be screened; 2) an incubation module, which incubates the prepared library with a solid support (magnetic beads or matrix) bound to the target; 3) an elution and collection module, which performs gradient elution of the RNA aptamer module bound to the target on the solid support with a buffer, and collects the eluate from each elution; 4) an optional concentration and purification module, which concentrates and purifies the RNA aptamers in the eluate; 5) a reverse transcription module, which reverse transcribes the RNA aptamer to obtain cDNA; 6) an amplification and high-throughput sequencing module, which performs amplification and high-throughput sequencing on the cDNA obtained above to obtain sequencing data; 7) An analysis module, which analyzes the sequencing data and ranks the candidate RNA aptamer sequences from high to low according to their binding potential, thereby obtaining RNA aptamer sequences with high binding affinity.

31. A biochip comprising the RNA aptamer according to any one of claims 25 to 28.

32. A method for manufacturing a biochip, comprising the following steps: 1) Screening and obtaining RNA aptamers using the method according to any one of claims 1 to 24; and 2) preparing a biochip using the RNA aptamers screened in step 1).

33. A pharmaceutical composition comprising the RNA aptamer according to any one of claims 25 to 28 and a pharmaceutically acceptable excipient or drug delivery carrier.

34. A drug delivery carrier, comprising the RNA aptamer according to any one of claims 25 to 28 connected thereto.

35. The drug delivery carrier according to claim 34, wherein The drug delivery vehicle is a liposome.

36. A diagnostic reagent comprising the RNA aptamer according to any one of claims 25 to 28 and other auxiliary reagents required for diagnosis.

37. Use of RNA aptamers screened by the method according to any one of claims 1 to 24 in the preparation of biochips, pharmaceutical compositions or diagnostic reagents.

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