A method for detecting microRNA based on surface-enhanced raman spectroscopy

Abstract

The application relates to a microRNA detection method based on surface-enhanced Raman spectroscopy, which comprises the following steps: covalently connecting two different DNA single chains modified by mercapto on the surface of gold nanoparticles respectively, and respectively modifying Raman reporter molecules, so as to respectively prepare two SERS probes, namely probe A and probe B. The probe A and the probe B are annealed and incubated with a sample to be detected containing microRNA, so as to obtain a sample solution to be detected. A certain amount of Raman spectra is collected from the sample solution to be detected, baseline treatment is carried out, and a Raman spectrum set is formed. The Raman spectrum set is subjected to digital quantitative calculation, and the concentration of the microRNA to be detected is calculated in combination with a standard curve. The application realizes rapid, high-sensitivity and repeatable quantitative detection of the microRNA, the detection method is simple and low in cost, can be completed by using a portable Raman spectrometer, and does not need to rely on a central laboratory and large equipment.

Description

Technical Field

[0001] This invention relates to the field of spectroscopic analysis and detection technology, and in particular to a method for detecting microRNA based on surface-enhanced Raman spectroscopy. Background Technology

[0002] Currently, cancer diagnosis mainly relies on imaging examinations and tissue biopsies, but these methods are significantly delayed and cannot achieve early screening and detection of cancer. Tumor development and progression begin at the molecular level, and molecular diagnostics, primarily based on nucleic acid detection, offers advantages such as high sensitivity, strong specificity, and non-invasiveness. MicroRNAs (miRNAs) are endogenous non-coding small RNA molecules that have been proven to play an important role in post-transcriptional gene regulation. Abnormal expression of miRNAs is closely related to cancer and represents a potential biomarker; therefore, establishing accurate and highly sensitive detection technologies for miRNAs is urgently needed.

[0003] Currently, methods for miRNA detection mainly include Northern blotting, microarrays, next-generation sequencing, quantitative reverse transcription polymerase chain reaction (RT-qPCR), loop-mediated isothermal amplification (LAMP), isothermal exponential amplification (EXPAR), rolling circle amplification (RCA), and ligase chain reaction (LCR). Among these methods, Northern blotting, as a traditional method, suffers from drawbacks such as long processing time, low sensitivity, and the need for large sample sizes. Microarrays are a high-throughput technology, but their detection sensitivity is low and their cost is high. Next-generation sequencing requires complex and expensive equipment and manpower, which does not meet clinical needs. Real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) is the most widely used nucleic acid amplification technology for miRNA detection. Other amplification technologies, including LAMP, EXPAR, RCA, and LCR, have high detection sensitivity, but the procedures are complex and time-consuming. Furthermore, due to the short chain length and high sequence similarity of miRNAs, it is difficult to design specific primers for different miRNAs, and false positives may occur during amplification. Therefore, there is an urgent need to develop a simple, rapid, highly sensitive, non-amplified miRNA diagnostic technology.

[0004] The current gold standard for miRNA detection is quantitative reverse transcription polymerase chain reaction (RT-qPCR). MiRNA quantification generally involves two steps: (i) synthesizing complementary DNA (cDNA) of the target miRNA using reverse transcriptase; and (ii) amplifying the cDNA by PCR using DNA polymerase and a pair of primers. The number of temperature cycles required to exceed the fluorescence threshold (Cq) is measured using real-time fluorescence monitoring technology and compared with a standard curve to quantify the target miRNA. Depending on the reverse transcription method, it can be divided into stem-loop RT-qPCR and multi-(A)-tailed RT-qPCR.

[0005] Surface-enhanced Raman spectroscopy (SERS) is a molecular spectroscopy technique with advantages such as ultra-high sensitivity, fingerprint specificity, and non-destructive detection. SERS quantitative technology has wide applications in chemical analysis, disease diagnosis, pathogen detection, environmental monitoring, and food safety. Furthermore, SERS quantitative technology has been widely used in liquid biopsy, including the detection of circulating tumor cells, exosomes, ctDNA, miRNA, and cancer-related proteins (Zhang, Y, et al. (2019). Theranostics.9(2):491-525). Traditional SERS quantitative methods extract the signal intensity of the characteristic peaks of interest in the SERS spectrum and establish a quantitative relationship between peak intensity and analyte concentration to detect unknown samples.

[0006] Patent CN113155807B discloses a highly sensitive miRNA detection method based on surface-enhanced Raman spectroscopy (SERS). First, gold-coated silver core-shell nanoparticles with the internal standard molecule 4-MBA and a silicon wafer containing gold nanoparticles are prepared as a two-dimensional substrate. A miRNA cyclic amplification system is used to prepare a capture probe that specifically recognizes miRNA. This capture probe couples the gold-coated silver core-shell nanoparticles to the two-dimensional substrate, resulting in a significant enhancement of the labeled molecule's Raman signal. This leads to highly sensitive SERS spectral detection results. The concentration of miRNA in the solution is calculated based on the ratio of the Raman signal intensity of the SERS probe to the second-order peak signal intensity on the silicon wafer. However, when quantifying ultra-low concentrations of analytes, the signal intensity (analog signal) of the SERS spectrum is easily affected by various factors, such as substrate inhomogeneity, hotspot distribution heterogeneity, background noise, and laser power fluctuations, resulting in poor quantitative repeatability.

[0007] To address this issue, Bi Xinyuan et al. first applied digital technology to liquid-phase SERS detection (Bi, X. et al. (2024). Nature. 628, 771–775). Similar to single-molecule detection technologies such as digital PCR and single-molecule enzyme-linked immunosorbent assay (SimoA), digital surface-enhanced Raman spectroscopy is based on the principle of single-molecule counting. It collects a large number of SERS spectra from different detection locations on a liquid colloidal substrate to form a spectral set. The SERS spectral signal intensity in each detection volume is converted into a digital signal of "0" or "1", i.e., a negative spectrum or a positive spectrum. Quantification is achieved by calculating the relationship between the proportion of positive spectra in the spectral set and the concentration.

[0008] The SERS colloid in the liquid phase digital SERS detection system has good dispersibility and uniformity, which effectively reduces the interference of signal intensity fluctuations at ultra-low concentrations, thereby improving the repeatability of SERS quantification at low concentrations and providing sensitivity for single-molecule detection.

[0009] Patent CN117783087A discloses a detection method based on time-dimensional Raman spectroscopy. This method involves preparing SERS colloidal particles; mixing the SERS colloidal particles with a sample in a liquid system to obtain a test liquid; using a Raman spectrometer to perform surface-enhanced Raman spectroscopy on the test liquid over time, collecting a certain number of Raman spectra to form a Raman spectrum set; and quantitatively calculating the concentration of the target molecule from the Raman spectrum set. However, current digital SERS detection methods are mainly used for the non-specific selection of small molecules, and have not achieved the quantitative detection of specifically captured biomolecules. Digital SERS detection strategies for miRNAs have not yet been developed and applied.

[0010] Therefore, establishing a simple, low-cost, highly sensitive, and reproducible method for the quantitative detection of miRNAs remains a significant challenge. Summary of the Invention

[0011] Existing non-amplified nucleic acid detection technologies, such as microarrays and Northern blotting, generally suffer from poor sensitivity. Due to the low abundance of miRNAs in blood, they are insufficient for clinical testing needs. RT-qPCR requires complex equipment and is costly, hindering point-of-care testing and low-cost implementation. Because miRNA sequences are short (19-25 bases), reverse transcription primer design is cumbersome. Stem-loop PCR offers high specificity and sensitivity for single miRNAs but cannot simultaneously reverse transcribe multiple miRNAs; multi-(A)-tailed PCR can simultaneously reverse transcribe multiple miRNAs, but its specificity is poor. Furthermore, different primers are required for different miRNAs, resulting in inconsistent amplification efficiencies. The relative abundance of different miRNAs changes after the RT-qPCR process, leading to deviations from the original sample and hindering clinical application.

[0012] SERS technology can achieve quantitative detection of non-amplified miRNAs, but at ultra-low concentrations, due to fluctuations in the electromagnetic field and uneven hotspots, the SERS signal intensity (analog signal) exhibits high variability and heterogeneity.

[0013] Therefore, establishing a simple, low-cost, highly sensitive, and reproducible method for the quantitative detection of miRNA remains a significant challenge. In view of the aforementioned deficiencies in existing technologies, this invention provides a miRNA detection method based on surface-enhanced Raman spectroscopy.

[0014] The objective of this invention can be achieved through the following technical solutions: This invention provides a method for detecting miRNA based on surface-enhanced Raman spectroscopy, comprising the following steps: S1: Preparation of functionalized SERS probes: Two different DNA single strands modified with thiol groups were covalently linked to the surface of gold nanoparticles and modified with Raman reporter molecules respectively to prepare two SERS probes, namely probe A and probe B; probe A and probe B can specifically capture target miRNA. S2: Incubation of SERS probes with target miRNA: Mix probe A and probe B with the target sample containing miRNA, anneal and incubate to obtain the test liquid; S3: SERS Spectral Acquisition and Processing: A certain number of Raman spectra are acquired from the liquid to be tested. The acquired Raman spectra are then processed to remove the baseline, forming a Raman spectral set. S4: Perform digital quantitative calculations on the Raman spectrum set and obtain the concentration value of the miRNA to be tested by combining it with the standard curve.

[0015] In one embodiment of the present invention, in step S1, the gold nanoparticles are gold nanoparticles modified with dipotassium di(p-sulfonylphenyl)phenylphosphine dihydrate (BSPP), and are referred to as SERS gold nanoparticles.

[0016] In one embodiment of the present invention, in step S1, the SERS gold nanoparticles have a particle size in the range of 12-15 nm, a maximum ultraviolet absorption peak of 523 nm, a narrow half-peak width, good dispersibility in the aqueous phase, and a uniform overall particle size distribution. The gold nanoparticles have stability for digital surface-enhanced Raman spectroscopy detection.

[0017] In one embodiment of the present invention, in step S1, the method of covalently linking thiol-modified DNA single strands (i.e., SH-ssDNA) on the surface of gold nanoparticles is as follows: tris(2-carboxyethyl)phosphine is added to the SH-ssDNA solution and incubated at room temperature to form an activated SH-ssDNA solution; then the activated SH-ssDNA solution is added to the gold nanoparticle solution to obtain a liquid phase system, and the system is shaken and incubated.

[0018] In one embodiment of the present invention, in step S1, the activated SH-ssDNA solution is added to the gold nanoparticle solution, and then phosphate buffer (PB) and sodium dodecyl sulfate (SDS) are added to obtain a liquid phase system, and the liquid phase system is shaken and incubated. The final concentration of the SERS gold nanoparticles in the liquid phase system is 0.1-1 nM; The final concentration of the SH-ssDNA in the liquid phase system is 0.1-1 μM; The final concentration of the phosphate buffer in the liquid phase system is 0.01-0.05 M; The sodium dodecyl sulfate has a mass fraction of 0.01% in the liquid phase system.

[0019] In one embodiment of the present invention, in step S1, the activated SH-ssDNA solution is added to the gold nanoparticle solution, and phosphate buffer and sodium dodecyl sulfate are added and mixed to obtain a liquid phase system. During the shaking incubation of the liquid phase system, sodium chloride solution is slowly added, and the final concentration of sodium chloride in the liquid phase system is 50-150 mM. The number of SH-ssDNA coupled to the surface of the gold nanoparticles is fixed by controlling the final sodium chloride salt concentration of the system. During the salt addition process, the liquid phase system is vortexed and sonicated to improve the coupling rate of SH-DNA.

[0020] In one embodiment of the present invention, in step S1, probe A and probe B are prepared by modifying DNA single strand a and DNA single strand b with gold nanoparticles, respectively; DNA single strand a and DNA single strand b are respectively complementary to half of the bases of the miRNA sequence to be tested.

[0021] In one embodiment of the present invention, in step S1, the Raman reporter molecules for probe A and probe B are the same; The Raman reporter molecule is selected from one of 4-nitrothiophenol (4-NBT), 4-mercaptobenzonitrile (4-MBN), or 4-mercaptobenzoic acid (4-MBA). Preferably, in step S1, the Raman reporter molecule is 4-nitrothiophenol (4-NBT).

[0022] Furthermore, the probe obtained using 4-NBT as a Raman reporter molecule was at 1335 cm⁻¹. -1 The relative standard deviation (RSD) of the characteristic peak intensity at that location is 6.4%.

[0023] In one embodiment of the present invention, in step S2, when probe A and probe B are mixed with the miRNA to be tested, the molar ratio of probe A and probe B is 1:1.

[0024] Preferably, in step S2, the final concentrations of probe A and probe B are 0.1-1 nM, and the concentration range of the miRNA to be tested is 0.1 pM-1 nM.

[0025] Preferably, in step S2, the annealing procedure is to heat the mixed solution to 60 °C and hold for 5 minutes, then cool it to room temperature at a rate of 0.1 °C / s; the incubation conditions are to incubate at room temperature for 30-60 minutes.

[0026] Preferably, in step S3, a certain number of Raman spectra are collected from the liquid to be tested using a Raman spectrometer, wherein the Raman spectrometer includes a confocal Raman spectrometer or a portable Raman spectrometer.

[0027] Preferably, in step S3, the test parameters of the Raman spectrometer are selected according to the SERS gold nanoparticles, and the test parameters include laser wavelength, power, and integration time.

[0028] In this invention, the method for spectral acquisition and processing in step S3 is as follows: the liquid to be tested is added to a capillary tube and a confocal Raman spectrometer or a portable Raman spectrometer is used for line scanning. The acquired spectra are then processed by airPLS to remove baselines, thereby obtaining a Raman spectrum set.

[0029] In one embodiment of the present invention, step S4 includes quantitative calculation including spectral threshold determination, spectral digitization, and positive spectral frequency statistics. The spectral threshold is calculated using a statistical maximum distribution method. The determination of the threshold includes the average value of the spectral noise region plus a certain number of times the standard deviation of the noise region. The spectral digitization determines the presence of target molecules according to the spectral thresholds: In a single sampling, if the analyte is present in the area irradiated by the laser spot, the particles assemble into dimers or polymers, and the characteristic peak signal intensity of the Raman reporter molecule in the SERS spectrum exceeds the set threshold, which is defined as "1" (i.e., positive spectrum); if the analyte is not present in the area irradiated by the laser spot, the particles are monodisperse, and the SERS intensity signal of the reporter molecule is less than the set threshold, which is defined as "0" (i.e., negative spectrum). The positive spectral frequency statistics include: counting the number of positive spectra and dividing by the total number of spectra to obtain the positive spectral frequency; establishing a linear relationship with the sample concentration to determine the concentration of the target molecule miRNA in the sample to be tested.

[0030] In this invention, the process for determining the spectral threshold is as follows: ① For each spectrum, use the maximum intensity within the characteristic peak region of the Raman reporter molecule ( I max The characteristic peak signal is used as the spectral range. The band range outside the characteristic peak signal region without obvious absorption peaks is selected as the noise region. In one embodiment of the invention, the characteristic peak region of the reporter molecule 4-NBT is 1315-1355 cm⁻¹. -1 The noise range is 1295-1315 cm. -1 and 1355-1375 cm -1 .

[0031] ② The spectral threshold is calculated by taking the average value of the noise region intensity. noise Add N times the standard deviation of the noise region intensity σ noise The calculated value of N is determined as follows: In digital computing, if the vast majority of signals are noise, then the signal strength follows a normal distribution ( X ~ N ( µ , σ 2 All intensity values ​​within the characteristic peak region are taken from this distribution sample, while the peak signal ( I max The value in the sample is then considered to be the maximum. The false positive probability is set to be less than 1 / k ( k (where the number of spectral lines collected is 0), obtained based on the maximum cumulative distribution function: ③ The characteristic peak region of 4-NBT is 1315-1355 cm⁻¹ -1 The original spectrum contains 16 intensity values ​​(n=16), and each digitized acquisition captures 1000 spectra, i.e. k =1000, setting the false positive probability to less than 1 / 1000. That is: ④ Since the standard deviation of spectral intensity differs at different wavenumbers, a correction factor is applied. r To determine the final value of N. The calculation yields... r = σ peak / σ noise 1.3 (the ratio of the standard deviation of the characteristic peak region to the noise region). Therefore, the value of N is determined to be 5 (3.85 × 1.3). That is, the spectral threshold is... noise +5 σ noise ; In this invention, the specific steps for digital quantification are as follows: ① For each spectrum, if the signal intensity of 4-NBT ( I max If the 4-NBT signal intensity is higher than the threshold, it is determined that a target molecule is present, and for this spectrum, the 4-NBT signal intensity is digitized as "1"; if the 4-NBT signal intensity ( I maxIf the signal intensity is below the threshold, it is determined that the target molecule does not exist, and the 4-NBT signal intensity of that spectrum is digitized as "0". The proportion of the total number of "1" spectra in each concentration spectrum set to the total number of spectra is counted, which is the frequency of positive spectra.

[0032] ② A quantitative standard curve for miRNA molecules was established using the frequency of positive spectra, enabling the quantification of miRNA molecules at unknown concentrations. Let the x-axis represent the concentration of the miRNA to be tested, and the y-axis represent the rate of occurrence of positive spectra. Logarithms to base 10 were taken for both axes, and the error bars were the standard deviations of the frequencies from three repeated tests at each concentration. The resulting linear fitting curve (log) was then obtained. y = k log x + b .

[0033] In one embodiment of the present invention, when the miRNA to be tested is miRNA-21, The nucleotide sequence of single-stranded DNA a (SH-ssDNA-a) is: SH-C6-TTTTTCAACATCAGT (5'-3' orientation). The nucleotide sequence of single-stranded DNA b (SH-ssDNA-b) is: CTGATAAGCTATTTT-C6-SH (5'-3' orientation). In one embodiment of the present invention, the detection limit of miRNA-21 is 10-100 fM.

[0034] Compared with the prior art, the present invention has the following beneficial effects: 1. Existing technologies struggle to achieve highly sensitive and reproducible quantitative detection of miRNAs under non-amplification conditions, especially in ultra-low concentration scenarios. Signal intensity-based SERS detection techniques generally suffer from poor reproducibility and insufficient detection accuracy. This invention utilizes digital surface-enhanced Raman spectroscopy to design and prepare functionalized gold nanoprobes. These probes exhibit excellent specificity and stability, enabling amplification-free, highly sensitive, and accurate detection of the biomarker miRNA-21. Furthermore, they can accurately quantify miRNA-21 extracted from human liver cancer cells, providing reliable and reproducible results.

[0035] 2. The detection method of this invention is compatible with portable Raman spectrometers, providing a simple and cost-effective miRNA detection solution. This solution eliminates the need for centralized laboratories and large-scale precision equipment, enabling point-of-care testing (POCT) of miRNAs and facilitating its widespread application in grassroots settings.

[0036] 3. The method of this invention employs a specific capture probe and reporter molecule strategy, successfully extending the application of digital SERS technology to the detection of macromolecular biomarkers and target molecules with inherently weak Raman scattering cross sections and low adsorption affinity. By changing the sequence of the DNA single strand, this method can be flexibly extended to the detection of other nucleic acid molecules, making it widely applicable. This detection method has broad application prospects in the field of point-of-care molecular diagnostics, especially suitable for point-of-care molecular diagnostic scenarios with high requirements for detection speed and convenience, such as the prevention and control of acute infectious diseases and pathogen screening, and has significant practical application value. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the SERS probe preparation and miRNA detection process.

[0038] Figure 2 Schematic diagram of TEM electron microscopy, UV absorption spectroscopy and hydrodynamic diameter characterization of BSPP-modified gold nanoparticles.

[0039] Figure 3 To assess the repeatability of the SERS probe signal.

[0040] Figure 4 This is a schematic diagram showing the UV-Vis absorption spectra and TEM characterization of the SERS probe after incubation with different concentrations of miRNA-21.

[0041] Figure 5 Schematic diagram of positive and negative spectra for detecting miRNA-21 (1 pM).

[0042] Figure 6 This is a schematic diagram of the digital SERS quantitative standard curve for the detection of miRNA-21 (0, 100 fM, 1 pM, 10 pM, 100 pM, 1 nM) by confocal Raman spectroscopy.

[0043] Figure 7 This is a schematic diagram of the digital SERS quantitative standard curve for the detection of miRNA-21 (0, 100 fM, 1 pM, 10 pM, 100 pM, 1 nM) using a portable Raman spectrometer. Detailed Implementation

[0044] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0045] Detection principle and process: The miRNA detection method based on surface-enhanced Raman spectroscopy includes the following steps: synthesis of gold nanoparticles, preparation of functionalized modified SERS probes, incubation of probes with target miRNAs, SERS spectral acquisition and processing, and quantitative calculation.

[0046] Specifically, the miRNA detection method based on surface-enhanced Raman spectroscopy includes the following steps: Step 1: Stable gold nanoparticles were prepared using the sodium citrate reduction method. Then, bis(p-sulfonylphenyl)phenylphosphine dipotassium salt (BSPP) dihydrate was used to replace the sodium citrate on the surface of the gold nanoparticles to obtain BSPP-modified gold nanoparticles.

[0047] Step 2: Surface modification of gold nanoparticles: Gold nanoparticles were mixed with thiol-modified DNA single-stranded molecules a (SH-ssDNA-a) and b (SH-ssDNA-b), respectively. Phosphate buffer and sodium dodecyl sulfate were added to form a liquid phase system, which was then incubated with sodium chloride and shaken. Raman reporter molecules (4-NBT) were then added to both liquid phase systems to synthesize two SERS probes specifically for capturing target miRNAs, namely probe A and probe B. Probe A and probe B are complementary to half of the bases in the target miRNA sequence.

[0048] Step 3: Mix SERS probes A and B with the miRNA to be tested in a liquid phase system, anneal, and then incubate. Step 4: SERS spectral acquisition and processing: Add the system to be tested into a capillary tube, use a Raman spectrometer to acquire a certain number of Raman spectra of the liquid to be tested, perform baseline removal processing on the acquired Raman spectra to form a Raman spectrum set.

[0049] Step 5: Perform digital quantitative calculations on the Raman spectrum set to obtain the concentration value of the miRNA to be tested: Quantitative calculation involves determining the analyte concentration in a single sampling session. If the analyte is present in the area illuminated by the laser spot, the particles assemble into dimers, and the characteristic peak signal intensity of the Raman reporter molecule exceeds a set threshold, defined as "1" (positive spectrum). If the analyte is absent in the laser-illuminated area, the particles are monodisperse, and the SERS intensity signal of the reporter molecule is less than a set threshold, defined as "0" (negative spectrum). By calculating the ratio of positive events (RPV), a linear relationship between the RPV and sample concentration can be obtained for quantitative analysis. Establishing a quantitative relationship between RPV and the concentration of known target molecules enables the detection of miRNAs in samples with unknown concentrations.

[0050] In a more specific embodiment of the present invention, a miRNA detection method based on surface-enhanced Raman spectroscopy includes the following steps: 1. Synthesis of BSPP-modified SERS gold nanoparticles: To meet the need for reproducible quantitative detection of ultra-low concentration target analytes using digital SERS technology, ideal SERS gold nanoparticles should possess the following properties: stable properties and good uniformity. Gold nanoparticles prepared by the sodium citrate reduction method are easy to synthesize and have a uniform particle size distribution. Gold nanoparticles obtained by replacing sodium citrate with dipotassium bis(p-sulfonylphenyl)phenylphosphine dihydrate (BSPP) exhibit good monodispersity and long-term storage stability, thereby ensuring sample reproducibility and meeting the requirements of digital SERS detection.

[0051] The preparation steps of BSPP-modified SERS gold nanoparticles are as follows: (1) Synthesis of gold nanoparticles by sodium citrate reduction method. First, a 1.165 mM chloroauric acid solution was prepared by dissolving 14.39 mg of chloroauric acid tetrahydrate (HAuCl4•4 H2O, analytical grade, Sinopharm Group) in 30 mL of ultrapure water.

[0052] Next, prepare a 34 mM sodium citrate aqueous solution (mass fraction 1%) by weighing 30 mg of trisodium citrate dihydrate (C6H7Na3O8•2 H2O, analytical grade, 99%, Sinopharm Group) and dissolving it in 3 mL of ultrapure water.

[0053] Finally, a reflux condenser was set up, and 30 mL of chloroauric acid solution (1.165 mM) was boiled. 3 mL of sodium citrate aqueous solution was quickly added, and the mixture was kept at a gentle boil and quickly mixed. The solution changed from light yellow to grayish purple, and after 1 minute it turned wine red. After boiling for another 40 minutes, citrate-modified gold particles were obtained. The citrate-modified gold particle (AuNPs) solution was cooled to room temperature, sealed and refrigerated for later use.

[0054] (2) Replacement of sodium citrate on the surface of gold nanoparticles with dipotassium bis(p-sulfonylphenyl)phenylphosphine dihydrate (BSPP, 97%, Aladdin): Add 3 mg BSPP to every 10 ml of AuNPs solution and shake overnight at room temperature. During shaking, slowly add sodium chloride solution to the AuNPs solution until the particle color changes from wine red to light purple. Centrifuge the resulting mixture at 6000 rpm for 15 minutes and remove the supernatant. Resuspend the precipitate in 0.5 ml of BSPP solution and mix with 0.5 ml of methanol. Centrifuge again, remove the supernatant, and resuspend in 3 mL of BSPP solution to obtain BSPP-modified gold nanoparticles. The particle size and concentration of BSPP-modified gold nanoparticles were estimated based on UV absorbance. BSPP replacement of citrate on the surface of gold particles can improve the stability and dispersibility of gold nanoparticles. When preparing SERS gold nanoparticles, you can refer to the literature Han, XG et al. (2011) Langmuir. 27(9), pp. 5282-5289.

[0055] 2. Preparation of functionalized SERS probes, including the following steps: (1) Dilute the SH-ssDNA storage solution with ultrapure water, mix 100 μL of SH-DNA (15 μM) with 2.5 μL of tris(2-carboxyethyl)phosphine (TCEP, 1 M) solution, and reduce at room temperature for 30-60 min.

[0056] (2) BSPP-modified gold nanoparticles were mixed with SH-ssDNA-a and SH-ssDNA-b, respectively, and then phosphate buffer and sodium dodecyl sulfate were added. NaCl was slowly added to the liquid phase system multiple times to increase the salt concentration through a "salt aging" process. The number of SH-DNA molecules coupled to the surface of the gold nanoparticles was fixed by controlling the final NaCl salt concentration of the system. The gold nanoparticles were vortexed and sonicated during the salt addition process to improve the coupling rate of SH-ssDNA molecules. The above reaction solution was centrifuged and washed five times to remove excess SH-ssDNA from the solution.

[0057] (3) After modifying SH-ssDNA-a and SH-ssDNA-b, a certain concentration of the Raman reporter molecule 4-nitrobenzenethiophenol (4-NBT) was added to each of the two solutions, followed by sonication for 30 s and incubation at room temperature to obtain functionalized SERS probes A and B. The final concentration of the Raman reporter molecule was the concentration required to achieve full adsorption on the surface of a single gold particle. The reporter molecule was attached to the remaining sites on the gold nanoparticles to obtain SERS-active capture probes A and B.

[0058] 3. Incubate the probe with the target miRNA, including the following steps: (1) Mix the prepared SERS probe A and probe B in a 1:1 ratio, then mix with different concentrations of the miRNA to be tested, then heat the solution to 60 °C and keep it for 5 minutes, then slowly cool it to room temperature, and incubate at room temperature for 30-60 minutes before collecting SERS spectra.

[0059] (2) By annealing the liquid-phase mixture, the hybridization efficiency of the SERS probe and the analyte is improved, and the non-specific adsorption is reduced, thereby reducing the false positive rate of detection.

[0060] 4. SERS spectral acquisition and processing: The instruments used included a confocal Raman spectrometer and a portable Raman spectrometer. Appropriate instrument parameters, such as laser wavelength, power, and integration time, were selected based on the gold nanoparticles. During the test, the liquid to be tested was placed in a suitable, transparent carrier container. A certain number of Raman spectra were collected from the liquid, and the baseline was removed from each SERS spectrum using the airPLS method.

[0061] 5. Quantitative calculation: Quantitative calculations involve three steps: determining the spectral threshold, spectral digitization, and statistical analysis of positive spectral frequencies. The spectral threshold can be determined scientifically and reasonably, including but not limited to the "mean + N standard deviations" for blank samples and the "mean + N standard deviations" for the same spectral noise region. Spectral digitization determines the presence of target molecules based on the spectral threshold; a signal intensity higher than the threshold indicates the presence of target molecules, defined as "1" (positive spectrum); a signal intensity lower than the threshold indicates the absence of target molecules, defined as "0" (negative spectrum). In signal frequency statistics, the number of spectra marked "1" is counted and divided by the total number of spectra to obtain the positive spectral frequency (positive spectrum ratio), thus establishing a relationship with the concentration of target molecules in the sample.

[0062] Example 1 miRNA-21 was detected using a 638 nm confocal Raman spectroscopy system, with BSPP-modified gold nanoparticles as the SERS substrate and 4-NBT as the Raman reporter molecule. Figure 1 This includes the preparation and assembly of SERS probes and the detection process for miRNAs.

[0063] The method in this embodiment specifically includes the following steps: (1) Preparation of BSPP modified gold nanoparticles: Refer to the above synthesis steps.

[0064] Characterization of BSPP-modified gold nanoparticles: See Figure 2The prepared gold nanoparticles have a particle size in the range of 12.0~15.0 nm, a maximum UV absorption peak of 523 nm, a narrow half-peak width, good dispersibility in aqueous phase, and a uniform overall particle size distribution. They also exhibit stability for digital surface-enhanced Raman spectroscopy detection.

[0065] (2) Preparation of functionalized SERS probes ① Mix 100 μL of 15 μM SH-ssDNA-a and SH-ssDNA-b (prepared by Sangon Biotech (Shanghai) Co., Ltd.) with 2.5 μL of 1 M tris(2-carboxyethyl)phosphonic acid hydrochloride (TCEP, Aladdin) and reduce at room temperature for 30-60 min. Mix SH-ssDNA with BSPP-modified gold nanoparticles, and add PB buffer and SDS. The final concentration of PB buffer in the system is 0.01 M, and the final concentration of SDS is 0.01%. Incubate at room temperature in the dark, slowly adding 1M NaCl solution during the process, with a final NaCl concentration of 50-150 mM. Vortex the mixture thoroughly after each addition of NaCl and sonicate for 10 s. After incubation, centrifuge 5 times to remove excess SH-ssDNA from the supernatant. ② Modification of Raman reporter molecules: The reporter molecule 4-NBT was added to AuNPs coupled with SH-ssDNA-a and b, and the mixture was sonicated for 30 s to ensure that 4-NBT was evenly distributed on the particle surface. Two SERS probes, A and B, were obtained.

[0066] For the repeatability of the SERS signal from probe A, see [link to relevant documentation]. Figure 3 , 10 SERS signal acquisition was performed by adding L probe A solution to a capillary quartz tube. In 30 samplings, SERS probe A was detected at 1335 cm⁻¹. -1 The relative standard deviation (RSD) of the characteristic peak intensity at the location is 6.4%, indicating that the probe signal has good repeatability.

[0067] The nucleic acid sequences involved in this embodiment are shown in the table below: Table 1. Nucleic acid names and sequences (3) Incubation of probe with target miRNA Probe A and probe B were mixed in a 1:1 ratio (final concentration 0.5 nM), and then mixed with different concentrations of the target miRNA (concentration gradient: 0 nM, 100 fM, 1 pM, 10 pM, 100 pM, 1 nM, 10 nM), with three parallel controls for each concentration. The reaction solution was then heated to 60 °C and held for 5 minutes, followed by slow cooling to room temperature. After incubation at room temperature for 30 minutes, SERS spectral analysis was performed.

[0068] Characterization: See Figure 4 When a high concentration of miRNA-21 (10 nM) was added, the maximum UV absorption peak of the particles shifted to red, confirming that the particles were successfully assembled. TEM characterization showed that when a low concentration of miRNA-21 (0.1 nM) was added, some particles assembled into dimer structures, while the unassembled particles showed good monodispersity.

[0069] (4) SERS spectral acquisition and data processing ① Take 10 μL of the test solution into a quartz capillary (outer diameter 2 mm, inner diameter 1 mm), place it in a confocal Raman spectrometer, and perform a point-by-point linear scan along the longitudinal axis of the capillary with a step size of 4 μm to collect 1000 SERS spectra to form a spectral set. The laser wavelength is 638 nm, the laser power is 12.67 mW, the integration time is 0.5 s, and the objective lens is 10x.

[0070] ② Perform baseline removal processing on the acquired SERS spectra using airPLS.

[0071] (5) Quantitative calculation ① Choose 1335 cm -1 The 4-NBT characteristic peak is located at [location missing]. For each spectrum, the 4-NBT characteristic peak region (1315-1355 cm⁻¹) is used. -1 Maximum strength within ) I max This is used as the characteristic peak signal. For each spectrum, the 1295-1315 cm⁻¹ value is calculated. -1 and 1355-1375 cm -1 The average peak area of ​​the blank noise region plus 5 times the standard deviation is used as the threshold. If the 4-NBT signal intensity is higher than the threshold, the target molecule is identified, and the 4-NBT signal of that spectrum is digitized as "1"; if the 4-NBT signal intensity is lower than the threshold, the target molecule is identified, and the 4-NBT signal of that spectrum is digitized as "0". The proportion of "1" spectra in each concentration spectral set to the total number of spectra is counted, i.e., the frequency of positive spectra.

[0072] The single spectra of positive spectrum "1" and negative spectrum "0" for detecting miRNA (1 pM) are as follows: Figure 5 As shown.

[0073] ② A quantitative standard curve for miRNA-21 at low concentrations was established by analyzing the relationship between positive spectral frequencies and concentrations, enabling the quantification of miRNA-21 at unknown concentrations. (Refer to...) Figure 6A 638 nm confocal Raman spectroscopy system was used to collect digital quantitative standard curves of different concentrations of miRNA-21 (points: the average positive ("1") spectral frequency value of three replicates for each concentration; error bars: the standard deviation of the frequency of three replicates for each concentration; the x-axis represents the concentration of the miRNA to be tested, and the y-axis represents the ratio of positive spectra). Taking the logarithm of both axes yielded a linear fitting curve: logy = k log x + b (R) 2 > 0.99, k =0.431, b =0.168). The positive spectral ratio of samples without analyte (0 nM) is defined as the false positive rate (RPE). False Substituting this into the linear standard curve, the detection limit is found to be 46 fM.

[0074] Example 2: miRNA-21 was detected using a 633 nm portable Raman spectrometer with BSPP-modified gold particles as the SERS substrate and 4-NBT as the Raman reporter molecule.

[0075] The steps are as follows: (1) preparation of gold nanoparticles, (2) synthesis of functionalized modified SERS probes, and (3) incubation of probes with the target miRNA, as described above.

[0076] (4) SERS spectral acquisition and data processing ① Take 10 μL of the test solution into a quartz capillary tube (outer diameter 2 mm, inner diameter 1 mm), place it in a portable Raman spectrometer, and perform a linear scan along the longitudinal axis of the capillary to collect 1000 SERS spectra to form a spectral set. The laser wavelength is 633 nm, the laser power is 30 mW, and the integration time is 0.1 s.

[0077] ② Perform baseline removal processing on the acquired SERS spectra using airPLS.

[0078] (5) Quantitative calculation ① Choose 1335 cm -1 The 4-NBT characteristic peak is located at [location missing]. For each spectrum, the 4-NBT characteristic peak region (1315-1355 cm⁻¹) is used. -1 Maximum strength within ) I max This is used as the characteristic peak signal. For each spectrum, the 1295-1315 cm⁻¹ value is calculated. -1 and 1355-1375 cm -1The average peak area of ​​the blank noise region plus 5 times the standard deviation is used as a threshold. If the 4-NBT signal intensity is higher than the threshold, the target molecule is identified, and the 4-NBT signal of the spectrum is digitized as "1"; if the 4-NBT signal intensity is lower than the threshold, the target molecule is identified, and the 4-NBT signal of the spectrum is digitized as "0". The proportion of "1" spectra in each concentration spectral set to the total number of spectra is counted, i.e., the frequency of positive spectra.

[0079] A quantitative standard curve for miRNA-21 at low concentrations was established by analyzing the relationship between positive spectral frequencies and concentration, enabling the quantification of ultra-low concentrations of miRNA-21. (Refer to...) Figure 7 Digital quantitative standard curves for miRNA-21 at different concentration gradients were acquired using a 633 nm portable spectrometer system (points: average positive ("1") spectral frequency values ​​from three replicates at each concentration; error bars: standard deviation of the frequencies from three replicates at each concentration; x-axis represents the concentration of the miRNA being tested, and y-axis represents the percentage of positive spectra). A linear fitting curve was obtained: log y = k log x + b (R) 2 > 0.99, k =0.353, b =0.121). The positive spectral ratio of samples without analyte (0 nM) is defined as the false positive rate (RPE). False Substituting this into the linear standard curve, the detection limit is found to be 52 fM.

[0080] Example 3: Using a 633 nm portable Raman spectrometer, BSPP-modified gold nanoparticles were used as the SERS substrate, and 4-NBT was used as the Raman reporter molecule to quantitatively detect miRNA-21 in HepG-2 cells. The steps are as follows: (1) preparation of gold nanoparticles, (2) synthesis of functionalized modified SERS probes, as described above.

[0081] (3) Extract miRNA from HepG-2 cells and measure the concentration of miRNA-21 in the samples using stem-loop RT-qPCR: ① HepG-2 adherent cells were cultured in a 3.5 cm diameter culture plate. 2 mL of trypsin was added to digest the cells, resulting in a cell suspension. Microscopic counting revealed a total cell count of approximately 5 × 10⁻⁶ cells. 6 indivual.

[0082] ② Total RNA was extracted from HepG-2 cells using a centrifugation column method. The purity of the RNA was detected using NanoDrop, and the absorbance ratio A260 / A280 was 2.03, indicating that the RNA extraction purity was good and the extraction efficiency was high.

[0083] ③ The miRNA-21 extracted was quantitatively extracted using the stem-loop RT-qPCR method, and the concentration of miRNA-21 in the sample was measured to be 63 pM.

[0084] (4) Incubation of probe with target miRNA Probe A and probe B were mixed in a 1:1 volume ratio (final concentration 0.5 nM), and then different concentrations of miRNA-21 standard solution (concentration gradient: 0, 100 fM, 1 pM, 10 pM, 100 pM, 1 nM) and cell-extracted RNA stock solution were added, ensuring that the volumes of standard solution and test RNA solution were the same. Three parallel controls were set up for each concentration. After annealing the mixture, it was incubated at room temperature.

[0085] (5) SERS spectral acquisition and data processing ① Take 10 μL of the test solution into a quartz capillary tube (outer diameter 2 mm, inner diameter 1 mm), place it in a portable Raman spectrometer, and perform a point-by-point linear scan along the longitudinal axis of the capillary to collect 1000 SERS spectra to form a spectral set. The laser wavelength is 633 nm, the laser power is 30 mW, and the integration time is 0.1 s.

[0086] ② Perform baseline removal processing on the acquired SERS spectrum set using airPLS.

[0087] (6) Quantitative calculation ① Choose 1335 cm -1 The 4-NBT characteristic peak is located at [location missing]. For each spectrum, the 4-NBT characteristic peak region (1315-1355 cm⁻¹) is used. -1 Maximum strength within ) I max This is used as the characteristic peak signal. For each spectrum, the 1295-1315 cm⁻¹ value is calculated. -1 and 1355-1375 cm -1The average peak area of ​​the blank noise region plus five times the standard deviation was used as a threshold. If the 4-NBT signal intensity was higher than the threshold, the target molecule was considered to be present, and the 4-NBT signal of that spectrum was digitized as "1"; if the 4-NBT signal intensity was lower than the threshold, the target molecule was considered to be absent, and the 4-NBT signal of that spectrum was digitized as "0". The proportion of "1" spectra in each concentration set to the total number of spectra was counted, i.e., the frequency of positive spectra. A quantitative standard curve for miRNA-21 molecules at low concentrations was established based on the relationship between the frequency of positive spectra and concentration.

[0088] ② The positive spectrum ratio of miRNA-21 extracted from cells was measured to be 9.3%, and the concentration of miRNA-21 in the sample was calculated to be 57 pM when substituted into the standard curve.

[0089] ③ To verify the accuracy of this detection method, the results of digital SERS detection (57 pM) and RT-qPCR detection (63 pM) were compared. There was no statistically significant difference in the quantitative results of the two methods, confirming the accuracy and reliability of digital SERS detection of miRNA.

[0090] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the disclosure of the present invention without departing from the scope of the invention should be within the protection scope of the present invention.

Claims

1. A method for detecting microRNA based on surface-enhanced Raman spectroscopy, characterized in that, Includes the following steps: S1: Preparation of functionalized SERS probes: Two different DNA single strands modified with thiol groups were covalently linked to the surface of gold nanoparticles and modified with Raman reporter molecules to prepare two SERS probes, namely probe A and probe B; probe A and probe B can specifically capture target microRNA. S2: Incubation of SERS probes with microRNA: Mix probe A and probe B with the sample containing microRNA, anneal the mixture and incubate to obtain the test liquid; S3: SERS Spectral Acquisition and Processing: A certain number of Raman spectra are acquired from the liquid to be tested, and the acquired Raman spectra are de-baseline processed to form a Raman spectral set; S4: Perform digital quantitative calculations on the Raman spectrum set and obtain the concentration value of the microRNA to be tested by combining it with the standard curve.

2. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 1, characterized in that, In step S1, the gold nanoparticles are gold nanoparticles modified with dipotassium dihydrate bis(p-sulfonylphenyl)phenylphosphine, and the particle size of the gold nanoparticles is 12.0-15.0 nm.

3. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 1, characterized in that, In step S1, the method for covalently linking thiol-modified DNA single strands to the surface of gold nanoparticles is as follows: Tris(2-carboxyethyl)phosphine was added to the SH-ssDNA solution and incubated at room temperature to form an activated SH-ssDNA solution; then the activated SH-ssDNA solution was added to the gold nanoparticle solution to obtain a liquid phase system, which was then shaken and incubated. The SH-ssDNA is a thiol-modified DNA single strand.

4. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 3, characterized in that, The activated SH-ssDNA solution was added to the gold nanoparticle solution, followed by the addition of phosphate buffer and sodium dodecyl sulfate to obtain a liquid phase system. The liquid phase system was then shaken and incubated. The final concentration of the gold nanoparticles in the liquid system is 0.1-1 nM; The final concentration of the SH-ssDNA in the liquid phase system is 0.1-1 μM; The final concentration of the phosphate buffer in the liquid phase system is 0.01-0.05 M; The sodium dodecyl sulfate has a mass fraction of 0.01% in the liquid phase system.

5. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 4, characterized in that, The activated SH-ssDNA solution was added to the gold nanoparticle solution, followed by the addition of phosphate buffer and sodium dodecyl sulfate to obtain a liquid phase system. During the shaking incubation of the liquid phase system, sodium chloride solution was slowly added, with the final concentration of sodium chloride in the liquid phase system being 50-150 mM.

6. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 1, characterized in that, In step S1, probe A and probe B are prepared by modifying DNA single strand a and DNA single strand b with gold nanoparticles, respectively; DNA single strand a and DNA single strand b are complementary to half of the bases of the microRNA sequence to be tested.

7. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 1, characterized in that, In step S1, the Raman reporter molecules for probe A and probe B are the same; The Raman reporter molecule is selected from one of 4-nitrobenzenethiophenol, 4-mercaptobenzonitrile, or 4-mercaptobenzoic acid.

8. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 1, characterized in that, In step S2, when probe A and probe B are mixed with the test sample containing microRNA, the molar ratio of probe A to probe B is 1:

1. Preferably, in step S2, the final concentrations of probe A and probe B are 0.1-1 nM, and the concentration range of the microRNA to be tested is 0.1 pM-1 nM. In step S2, the annealing procedure is as follows: heat the mixed solution to 60 °C and hold for 5 minutes, then cool it to room temperature at a rate of 0.1 °C / s; the incubation conditions are room temperature incubation for 30-60 minutes.

9. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 1, characterized in that, In step S4, the quantitative calculation includes spectral threshold determination, spectral digitization, and positive spectral frequency statistics; the spectral threshold is calculated using a statistical maximum distribution method, and the threshold determination includes the average value of the spectral noise region plus a certain number of times the standard deviation of the noise region; The spectral digitization determines the presence of a target molecule based on the spectral threshold: in a single sampling, if the maximum signal intensity in the characteristic peak region of the reported molecule is higher than the spectral threshold, it is determined that a target molecule exists and is defined as "1", i.e., a positive spectrum; in a single sampling, if the maximum signal intensity in the characteristic peak region of the reported molecule is lower than the spectral threshold, it is determined that no target molecule exists and is defined as "0", i.e., a negative spectrum. The positive spectral frequency statistics include: counting the number of positive spectra and dividing by the total number of spectra to obtain the positive spectral frequency, establishing a linear relationship with the sample concentration, thereby determining the concentration value of the target molecule microRNA in the sample to be tested.

10. The microRNA detection method based on surface-enhanced Raman spectroscopy according to claim 9, characterized in that, The process for determining the spectral threshold is as follows: ① For each spectrum, use the maximum intensity within the characteristic peak region of the Raman reporter molecule ( I max The characteristic peak signal is selected as the signal region; the band range outside the characteristic peak signal region without obvious absorption peaks is selected as the noise region. ② By calculating the average value of the noise intensity in the area noise Add N times the standard deviation of the noise region intensity σ noise The spectral threshold is calculated; The specific steps for digital quantification are as follows: ① For each spectrum, if the signal intensity ( I max If the signal intensity is higher than the threshold, it is determined that a target molecule is present, and for this spectrum, the signal intensity is digitized as "1"; if the signal intensity ( I max If the signal intensity is below the threshold, it is determined that there is no target molecule, and the signal intensity of the spectrum is digitized as "0". The proportion of the total number of "1" spectra in each concentration spectrum set to the total number of spectra is counted, which is the frequency of positive spectra. ② A quantitative standard curve for microRNA molecules was established using positive spectral frequencies to quantify microRNA molecules at unknown concentrations. The x-axis represents the concentration of the microRNA to be tested, and the y-axis represents the rate of occurrence of positive spectra. Logarithms to base 10 were taken for both axes, and the error bars were the standard deviations of the frequencies from three repeated tests at each concentration. The linear fitting curve logy = ... k log x + b .

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