Surface enhanced Raman detection method for amino acid

Abstract

The invention belongs to the field of Raman detection, and particularly relates to a surface-enhanced Raman detection method for amino acid and a detection substrate thereof. According to the amino acid concentration detection method based on the low-frequency Raman scattering combined surface enhancement technology and the detection substrate thereof, the problems of low sensitivity, long consumed time, high cost and the like in the existing amino acid detection technology are effectively solved. By designing surface enhanced Raman scattering nano-particles without low-frequency Raman interference signals, namely double-sphere structure nano-particles composed of gold nano-spheres and ferroferric oxide nano-spheres, and combining with a magnetic aggregation substrate, high-sensitivity and rapid detection of various amino acids is realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of Raman detection, and particularly relates to a surface-enhanced Raman detection method for amino acids and a detection substrate thereof. BACKGROUND

[0002] Amino acids are essential nutrients for the human body, as the basic building blocks of proteins, they play a core role in the growth and development, cell repair and tissue renewal of the human body. Amino acids are involved in the synthesis of enzymes, hormones, antibodies and other bioactive substances, and regulate the metabolism, immunity and physiological functions of the human body. In addition, certain amino acids are also involved in the synthesis of neurotransmitters, affecting mood and cognitive function. However, abnormal elevation of amino acids is also closely related to a variety of diseases, and the mechanism involves genetic defects, organ dysfunction or metabolic disorders. Genetic amino acid metabolic disorder diseases, these diseases are mainly caused by gene mutations to cause defects in specific amino acid metabolic enzymes, leading to abnormal accumulation of amino acids in the body, such as phenylketonuria (abnormal metabolism of phenylalanine), histidineemia (abnormal metabolism of histidine), arginemia (abnormal metabolism of arginine). Secondary amino acid elevation caused by liver and kidney diseases, such as tyrosine elevation caused by cirrhosis, abnormal elevation of branched-chain amino acids in plasma caused by renal failure. There is a two-way relationship between amino acid metabolism abnormalities and diabetes, insulin resistance or insufficient secretion can affect branched-chain amino acid (BCAA) metabolism, leading to elevated BCAA levels in the blood, further exacerbating insulin resistance, forming a vicious cycle. Long-term abnormal amino acid levels can harm cardiovascular health, and excess amino acids (such as homocysteine) can damage vascular endothelium, promote atherosclerosis, increase the risk of thrombosis, and increase the risk of heart disease and stroke.

[0003] Therefore, Determining the content and dynamic changes of multiple amino acids in human body fluids plays a crucial role in medical, neurological and physiological research, and is also of great significance for the accurate diagnosis of various diseases and the scientific regulation of related therapeutic drug doses. Currently, the detection methods for amino acids mainly include electrochemical detection, high-performance liquid chromatography and enzyme-linked immunosorbent assay. However, due to the low content of free amino acids in biological samples and the complex and variable environment, there are many interfering molecules, and these traditional methods generally have the limitations of insufficient sensitivity, long detection time and high cost. Therefore, developing a multiple amino acid detection technology with high sensitivity, rapid response and significant cost-effectiveness has become a key issue that needs to be tackled in the medical field.

[0004] Raman spectroscopy is known for its rapid, simple and non-destructive detection characteristics. In particular, surface-enhanced Raman scattering (SERS) technology ingeniously uses the plasmonic effect of the surface of noble metals to significantly amplify the Raman signal, thereby greatly improving the detection sensitivity and even enabling single-molecule level detection. Therefore, SERS technology has attracted widespread attention from researchers and has shown broad application prospects in food detection, disease diagnosis, environmental monitoring, and chemical analysis and other fields. However, it is worth noting that most of the current Raman scattering detection of amino acids focuses on the high-frequency region (>200 cm - ¹), resulting in relatively limited detection accuracy, which is difficult to meet the strict requirements of medical detection. The inventors found that many amino acids have strong low-frequency Raman, and the noble metal nanoparticle SERS detection substrate prepared by the mainstream sodium citrate reduction method has strong interference signals in the low-frequency part (<200 cm -1 ). SUMMARY

[0005] In order to solve the problem that the detection accuracy of amino acids is not high at present, the present application provides a detection method for the concentration of multiple amino acids based on low-frequency Raman scattering combined with surface-enhanced technology and a detection substrate thereof.

[0006] The technical solution to achieve the purpose of the present application is: a surface-enhanced Raman detection substrate without low-frequency Raman interference signals, comprising surface-enhanced Raman scattering (SERS) nanoparticles and a magnetic aggregation substrate, wherein the surface-enhanced Raman scattering nanoparticles are double-sphere structure nanoparticles composed of gold nanospheres and ferroferric oxide nanospheres; the magnetic aggregation substrate comprises single-crystal silica flakes and a neodymium-iron-boron magnet; and no sodium citrate with strong low-frequency signals is added during the preparation of the surface-enhanced Raman scattering nanoparticles.

[0007] Further, in the surface-enhanced Raman scattering nanoparticles, the diameter of the gold nanospheres is 10-15 nm, and the diameter of the ferroferric oxide nanospheres is 15-20 nm.

[0008] Further, the mass ratio of the gold nanospheres to the ferroferric oxide nanospheres is 1-3:1.

[0009] Further, the surface-enhanced Raman scattering nanoparticles have an ultraviolet-visible absorption peak around 520 nm, which can resonate with common laser with a wavelength of 514.5 nm.

[0010] Further, in the surface-enhanced Raman scattering nanoparticles, the optimal crystal face orientation of the ferroferric oxide is (111), and the optimal crystal face orientation of the gold is (100).

[0011] Further, the surface-enhanced Raman scattering nanoparticles are modified by silane, and the amino silane is obtained by the reaction of 3-aminopropyltrimethoxysilane (APTMS) and ammonia.

[0012] Further, the gold nanospheres are reduced by oleic acid amine as a reducing agent.

[0013] Further, the monocrystalline silica flakes in the magnetic aggregation substrate have no obvious low-frequency Raman signal, and the residual magnetism of the neodymium-iron-boron magnet is greater than 11 kilogauss.

[0014] The application further provides a surface-enhanced Raman detection method for amino acids, which comprises the following steps: mixing and adsorbing the surface-enhanced Raman scattering nanoparticles and a solution containing to-be-detected amino acids, and then placing the mixture into the magnetic aggregation substrate to form a surface-enhanced Raman scattering nanoparticle aggregation area on the surface of the monocrystalline silica, and measuring the low-frequency Raman spectrum of the aggregation area after drying.

[0015] Further, the amino acids include one of cysteine, histidine, aspartic acid, arginine, phenylalanine, serine, tyrosine, alanine, methionine and isoleucine.

[0016] Further, the solution containing to-be-detected amino acids is a body fluid sample, and after the surface-enhanced Raman scattering nanoparticles are mixed and adsorbed with the body fluid sample, the body fluid sample needs to be pretreated in the following manner to remove biological macromolecules: the body fluid sample is placed in a centrifugal ultrafiltration tube and centrifuged at 5000-10000 rpm for 2-10 minutes, and the liquid at the bottom of the ultrafiltration tube is taken as the to-be-detected sample. The molecular cut-off of the centrifugal ultrafiltration tube is ≤ 3 kDa.

[0017] Further, the surface-enhanced Raman scattering nanoparticles and the solution containing to-be-detected amino acids are mixed in a volume ratio of 1:10.

[0018] Further, the measurement wave number of the low-frequency Raman spectrum is limited to 30-200 cm -1 ; and the obtained low-frequency Raman spectrum is compared with the low-frequency Raman spectrum of a standard amino acid sample, so that the concentration of the to-be-detected amino acid with a strong low-frequency Raman signal can be obtained, wherein the Raman laser wavelength matches the ultraviolet-visible absorption peak of the surface-enhanced Raman scattering nanoparticles.

[0019] Compared with the prior art, the application has the following beneficial effects: Firstly, the amino acid concentration detection method based on low-frequency Raman scattering combined with surface enhancement technology and the detection substrate thereof provided by the application effectively solve the problems of low sensitivity, long time consumption and high cost in the existing amino acid detection technology. By designing surface-enhanced Raman scattering nanoparticles without low-frequency Raman interference signals, i.e., double-ball structure nanoparticles composed of gold nanospheres and ferroferric oxide nanospheres, and combining with a magnetic aggregation substrate, high-sensitivity and rapid detection of various amino acids is realized. The detection substrate not only avoids the interference signals of traditional noble metal nanoparticles in the low-frequency part, but also further improves the accuracy and reliability of detection by optimizing the size, crystal face orientation and surface modification of the nanoparticles.

[0020] Secondly, the detection limit of the method for detecting amino acids based on surface-enhanced low-frequency Raman scattering provided by the application can reach less than 10 -4 M. The method is not only suitable for the detection of complex body fluid samples such as serum and cerebrospinal fluid, but also simple and rapid to operate, without complex sample pretreatment steps, greatly shortening the detection time and reducing the detection cost. Therefore, the application has wide application prospects in medical, neurological and physiological research, diagnosis of various diseases and control of related therapeutic drugs, and provides a new powerful tool for accurate detection of amino acids. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings are not intended to be drawn to scale. In the drawings, corresponding operating steps in each figure are labeled in the figure by text. For the sake of clarity, not every step part is described in each figure. Embodiments of various aspects of the application will now be described by way of example with reference to the accompanying drawings, in which: Figure 1 Raman spectra of various amino acid powders and theoretical calculation results; Figure 2 Raman detection schematic diagram in the embodiment of the application; Figure 3 Preparation process of the magnetic aggregation substrate in the embodiment of the application; Figure 4 Transmission electron microscope image of the surface-enhanced Raman scattering nanoparticles in the embodiment of the application; Figure 5 Ultraviolet-visible absorption spectrum of the surface-enhanced Raman scattering nanoparticles in the embodiment of the application; Figure 6 a is the SERS detection result of the standard sample containing different concentrations of phenylalanine in application example 1 of the application; Figure 6 b is the SERS detection result of the sample simulating the human body fluid environment (artificial cerebrospinal fluid) in application example 1 of the application; Figure 7a is the SERS detection result of the standard sample containing different concentrations of aspartic acid in application example 2 of the present application; Figure 7 b is the SERS detection result of the sample simulating the human body fluid environment (artificial cerebrospinal fluid) in application example 2 of the present application; Figure 8 Raman spectra of sodium citrate, Au NPS prepared by sodium citrate reduction method, and amino-modified Au-Fe304 NPS used in the present application. DETAILED DESCRIPTION

[0022] In order to better understand the technical content of the present application, specific embodiments are described below with reference to the accompanying drawings.

[0023] Aspects of the present application are described in this patent application with reference to the accompanying drawings, in which are shown a number of illustrative embodiments. The embodiments of the present application described herein are not meant to be an all-inclusive explanation of the application of the present application. It is to be understood that the various concepts and embodiments introduced above and those described below can be implemented in any of numerous ways, as the disclosed concepts and embodiments are not limited to any particular manner of implementation. Additionally, some aspects of the present application can be utilized independently of other aspects of the present application, for any suitable purpose.

[0024] The present application utilizes a method for identifying a plurality of amino acids by low-frequency Raman. According to the Raman detection experiment, it is found that a plurality of amino acids have very strong low-frequency Raman signals, which are one order of magnitude stronger than high-frequency Raman signals. Combined with theoretical calculation, it is found that due to the special molecular structure, a plurality of amino acids have very strong low-frequency Raman peaks (<200 cm -1 ), which are one order of magnitude stronger than high-frequency Raman peaks (>200 cm -1 ). It is proved that the low-frequency Raman signals are caused by the torsional vibration of the C-C bond on the side chain of the corresponding amino acid molecule, which is the intrinsic signal of the corresponding molecule, and can be used to identify the presence of a plurality of amino acids. The existing detection of a plurality of amino acids based on Raman spectrum is measured by high-frequency Raman peaks.

[0025] The inventors first explored the origin of the low-frequency Raman of a plurality of amino acids. First, the inventors detected the Raman spectrum of the powder sample of the amino acid by using the T64000 Raman spectrometer of HORIBA company, and used an argon ion laser with a wavelength of 514.5 nm (green light) as the detection light source. The strongest peak in the low-frequency region (<200 cm -1 ) is one order of magnitude stronger than that in the high-frequency region (>200 cm -1) one order of magnitude or more. Secondly, the inventors use the B3LYP method in the density functional theory (DFT) to optimize the structure of various amino acids at the 6-311G** base group level by using the Gaussian09 quantum chemistry calculation software, and calculate the Raman vibration intensity according to the frequency, temperature and Raman activity of incident light: Raman vibration intensity calculation formula: (1), wherein, , and represent the Raman activity, Raman intensity and vibration frequency (cm -1 ) of the first i vibration mode, is the frequency of incident light (cm -1 ), is the temperature, is the Planck constant, is the Boltzmann constant, is the speed of light, is a constant coefficient, is the concentration coefficient of the material. When the incident light and the temperature are fixed, the Raman intensity is only related to the Raman activity and the vibration frequency .

[0026] The calculation results show that various amino acids have very strong low-frequency Raman signals, and the signals originate from the torsional vibration of the two C-C bonds on the tail chain of the ring chain structure molecule. The two torsional vibrations cause a great change in the distribution of electron cloud density, further causing a change in the molecular polarizability, thereby producing very strong low-frequency Raman spectra. Among them, Figure 1 the Raman spectrum test results and theoretical calculation results of various standard amino acid samples are given. The surface enhanced Raman detection method of the various amino acids described in the application is as shown in Figure 2 , comprising the following steps: S1, testing the low-frequency Raman spectrum of the standard amino acid sample.

[0027] S11, mixing the amino acid with the body fluid to form a mixed solution with a standard concentration, centrifuging in a centrifugal ultrafiltration tube at 8000 rpm for 5 minutes to remove macromolecular impurities, and taking the liquid at the bottom of the ultrafiltration tube as a standard sample, wherein the molecular cut-off of the centrifugal ultrafiltration tube is ≤ 3 kDa.

[0028] S12, mixing the standard sample with the surface enhanced Raman scattering nanoparticle sol in the example according to a volume ratio of 10:1, and placing it into the magnetic aggregation substrate for enrichment. After sufficient adsorption, the magnetic aggregation substrate is taken out and dried in a blast drying oven at 60 oDry at C for 10 minutes until a dry aggregated area is formed.

[0029] S13 uses an argon-ion laser with a wavelength of 514.5 nm (green light) as the detection light source, and the detection wavenumber is limited to 30~200 cm⁻¹. -1 Between these points, low-frequency Raman spectra were measured at the aforementioned aggregation points to obtain the low-frequency Raman spectra of the standard amino acid samples.

[0030] S2 test low-frequency Raman spectra of body fluid samples containing the amino acids to be tested.

[0031] S21. Centrifuge the body fluid sample containing the amino acid to be tested in a centrifugal ultrafiltration tube at 8000 rpm for 5 minutes to remove large molecular impurities. Take the liquid at the bottom of the ultrafiltration tube as the sample to be tested. The molecular cutoff of the centrifugal ultrafiltration tube is ≤ 3kDa.

[0032] S22, the sample to be tested is mixed with the surface-enhanced Raman scattering nanoparticle sol from the example at a volume ratio of 10:1, and then placed in the magnetic aggregation substrate for enrichment. The fully adsorbed magnetic aggregation substrate is then removed and dried in a forced-air drying oven at 60°C. o Dry at C for 10 minutes until a dry aggregated area is formed.

[0033] S23 uses an argon-ion laser with a wavelength of 514.5 nm (green light) as the detection light source, and the detection wavenumber is limited to 30~200 cm⁻¹. -1 Between these points, low-frequency Raman spectra are measured at the aforementioned aggregation points to obtain the low-frequency Raman spectra of the sample to be tested.

[0034] S3. By comparing the low-frequency Raman spectrum of the sample to be tested obtained in S2 with the low-frequency Raman spectrum of the standard sample obtained in S1, the actual concentrations of various amino acids in the sample to be tested can be obtained.

[0035] The position of the UV-Vis absorption peak is determined by the size of the gold particles, increasing with the increase of the gold particle diameter. In this invention, the surface-enhanced Raman scattering nanoparticles are double-sphere nanoparticles composed of gold nanospheres and iron oxide nanospheres. The UV-Vis absorption peak of the surface-enhanced Raman scattering nanoparticles can be determined to be at approximately 520 nm based on particle size calculations and spectral detection. During Raman spectroscopy testing, a Raman laser wavelength of 514.5 nm was selected to match the UV-Vis absorption peak position of 520 nm for the surface-enhanced Raman scattering nanoparticles.

[0036] Example like Figure 3 As shown, this embodiment provides a surface-enhanced Raman detection substrate. The surface-enhanced Raman detection substrate comprises two parts: surface-enhanced Raman scattering nanoparticles and a magnetically aggregated substrate.

[0037] Surface-enhanced Raman scattering nanoparticles preparation: 20 mL of octadecene, oleic acid (6 mmol), oleylamine (6 mmol) and hexadecanediol (10 mmol) were added into a three-necked round-bottom flask, stirred and gradually heated to 120℃, and kept at this temperature for 20 minutes. Subsequently, iron pentacarbonyl (Fe3(CO)5, 2 mmol) was added into the reaction vessel, and stirring was continued for 3 minutes. Then, chloroauric acid trihydrate (HAuCl4·3H2O, 40 mg) was mixed with oleylamine (4.5 mmol) to obtain a uniform wine-red solution without precipitate. The wine-red solution was added into the flask, and the color of the mixture immediately changed to deep red. The temperature was raised to 310℃, and then refluxed for 40 minutes. After stopping heating, the reaction mixture was cooled to room temperature under nitrogen atmosphere. A small amount of isopropanol was added to precipitate the nanoparticles, which were then centrifuged at 10,000 rpm for 5 minutes to remove the supernatant. The precipitate was washed with anhydrous ethanol until the supernatant became colorless and transparent, and the precipitate was the Au-Fe3O4 bi-sphere nanoparticles.

[0038] The nanoparticles were ultrasonically dispersed in 100 mL of distilled water, heated to 60℃, 1 mL of ammonia water (25% concentration) and 100 µL of 3-aminopropyltrimethoxysilane (APTMS) were added, and mechanically stirred for 90 minutes. After natural cooling to room temperature, the amino-modified Au-Fe3O4 bi-sphere nanoparticles, i.e. the SERS enhancement nanoparticles, were obtained.

[0039] The transmission electron microscopy of the SERS enhancement nanoparticles is shown in Figure 4 Figure 4 The surface-enhanced Raman scattering nanoparticles are regular bi-spheres, with the smaller and darker being gold nanospheres and the larger and lighter being Fe3O4 nanospheres. The corresponding ultraviolet-visible absorption spectrum is shown in Figure 5

[0040] Application Example 1: This application example is based on the detection of different concentrations of phenylalanine in a simulated human body fluid environment by surface-enhanced low-frequency Raman scattering. The human body fluid environment in this application example is simulated by artificial cerebrospinal fluid (pH = 7.4).

[0041] 1. Test the low-frequency Raman spectrum of the standard phenylalanine sample.

[0042] (1) Prepare a PBS buffer solution (pH = 7.4) and phenylalanine powder with a concentration of 10 -1 M, 10 -2 M, 10 -3 M and 10​​-4 A simulated body fluid mixture of M was used as the standard test sample.

[0043] (2) The standard test sample and the surface-enhanced Raman scattering nanoparticle sol in the examples were mixed at a volume ratio of 10:1. The mixture was then placed in the magnetic aggregation substrate for enrichment. After sufficient adsorption, the magnetic aggregation substrate was removed and dried in a forced-air drying oven at 60°C. o Dry at C for 10 minutes until a dry aggregated area is formed.

[0044] (3) Using an argon-ion laser with a wavelength of 514.5 nm (green light) as the detection light source, the low-frequency Raman spectrum of the above-mentioned aggregation point was measured, and the test results are as follows: Figure 6 As shown in a. From Figure 6 As can be seen from a, the low-frequency signal of samples with different phenylalanine concentrations is stronger than that of the high-frequency signal, and the detection limit (signal-to-noise ratio <3) in the low-frequency range can reach 10. -4 M.

[0045] 2. Test the low-frequency Raman spectrum of artificial cerebrospinal fluid samples containing phenylalanine.

[0046] (1) Add 10 to the artificial cerebrospinal fluid sample -3 M contains phenylalanine to simulate abnormal phenylalanine concentrations in the human body.

[0047] (2) Centrifuge the artificial cerebrospinal fluid sample at 8000 rpm for 5 minutes in a centrifugal ultrafiltration tube to remove macromolecular impurities. Take the liquid at the bottom of the ultrafiltration tube as the sample to be tested. The molecular cutoff of the centrifugal ultrafiltration tube is ≤ 3 kDa.

[0048] (3) The sample to be tested was mixed with the surface-enhanced Raman scattering nanoparticle sol in the examples at a volume ratio of 10:1, and then placed in the above-mentioned magnetic aggregation substrate for enrichment. The fully adsorbed magnetic aggregation substrate was then removed and dried in a forced-air drying oven at 60°C. o Dry at C for 10 minutes until a dry aggregated area is formed.

[0049] (4) An argon ion laser with a wavelength of 514.5 nm (green light) was used as the detection light source, and the detection wavenumber was limited to 30~200 cm⁻¹. -1 Between these points, low-frequency Raman spectra are measured at the aforementioned aggregation points to obtain the low-frequency Raman spectra of the sample to be tested.

[0050] 3. Detect the concentration of phenylalanine in the sample.

[0051] By comparing the low-frequency Raman spectrum of the sample to be tested with that of the standard sample, the actual concentration of phenylalanine in the sample can be determined. It can be seen that the intensity of the characteristic peak of phenylalanine in the low-frequency Raman spectrum of this sample is similar to that of 10... -3The Raman peak intensities of the standard samples with different M concentrations are comparable, as shown in Figure 6 b. This indicates that this technique can effectively detect abnormal increases in phenylalanine concentration in artificial cerebrospinal fluid samples.

[0052] Application Example 2: This application example is based on surface-enhanced low-frequency Raman scattering to detect aspartic acid with different concentrations in a simulated human body fluid environment. The human body fluid environment in this application example is simulated by artificial cerebrospinal fluid (pH = 7.4).

[0053] 1. Test the low-frequency Raman spectrum of the standard aspartic acid sample.

[0054] (1) Use PBS buffer solution (pH = 7.4) and aspartic acid powder to prepare simulated body fluid mixtures with concentrations of 10 -1 M, 10 -2 M, 10 -3 M, and 10 -4 M as standard samples to be tested.

[0055] (2) Mix the standard samples to be tested with the surface-enhanced Raman scattering nanoparticle sol of the example according to the volume ratio of 10:1. Place it in the magnetic aggregation substrate for enrichment. After sufficient adsorption, take out the magnetic aggregation substrate and dry it in a blast drying oven at 60 o C for 10 minutes until a dry aggregation zone is formed.

[0056] (3) Use an argon ion laser with a wavelength of 514.5 nm (green light) as the detection light source to measure the low-frequency Raman spectrum of the above aggregation points. The test results are shown in Figure 7 a. As can be seen from Figure 7 a, the low-frequency signals of samples with different aspartic acid concentrations are stronger than the high-frequency signals, and the detection limit (signal-to-noise ratio <3) of the low-frequency band can reach 10 -4 M.

[0057] 2. Test the low-frequency Raman spectrum of the artificial cerebrospinal fluid sample containing aspartic acid.

[0058] (1) Add 10 -3 M of aspartic acid to the artificial cerebrospinal fluid sample to simulate abnormal aspartic acid concentration in the human body.

[0059] (2) Centrifuge the artificial cerebrospinal fluid sample in a centrifugal ultrafiltration tube at 8000 rpm for 5 minutes to remove macromolecular impurities. Take the liquid at the bottom of the ultrafiltration tube as the sample to be tested. The molecular cut-off of the centrifugal ultrafiltration tube is ≤ 3 kDa.

[0060] (3) The sample to be tested was mixed with the surface-enhanced Raman scattering nanoparticle sol in the examples at a volume ratio of 10:1, and then placed in the above-mentioned magnetic aggregation substrate for enrichment. The fully adsorbed magnetic aggregation substrate was then removed and dried in a forced-air drying oven at 60°C. o Dry at C for 10 minutes until a dry aggregated area is formed.

[0061] (4) An argon ion laser with a wavelength of 514.5 nm (green light) was used as the detection light source, and the detection wavenumber was limited to 30~200 cm⁻¹. -1 Between these points, low-frequency Raman spectra are measured at the aforementioned aggregation points to obtain the low-frequency Raman spectra of the sample to be tested.

[0062] 3. Detect the concentration of aspartic acid in the sample.

[0063] By comparing the low-frequency Raman spectrum of the sample to be tested with that of the standard sample, the actual concentration of aspartic acid in the sample can be determined. The intensity of the characteristic peak of aspartic acid in the low-frequency Raman spectrum of the sample can be observed to be similar to that of a standard sample. -3 The Raman peak intensities of the standard samples with concentration M are comparable, such as Figure 7 As shown in b, this indicates that the technique can effectively detect abnormal increases in aspartic acid concentration in artificial cerebrospinal fluid samples.

[0064] Figure 8 Raman spectra of Au NPs prepared by sodium citrate reduction and amino-modified Au-Fe3O4 NPs used in the embodiments of the invention are shown. The results indicate that sodium citrate exhibits strong low-frequency Raman peaks, and the Au NPs prepared by sodium citrate reduction also show low-frequency Raman signals. Therefore, Au NPs prepared by sodium citrate reduction are not suitable for low-frequency SERS measurements. The amino-modified Au-Fe3O4 NPs used in the embodiments of the invention did not show significant Raman signals in the low-frequency region; the two lowest vibrational frequencies (212 and 273 cm⁻¹) were observed. -1 The molecular vibrations attributed to Fe3O4 are suitable for the detection of low-frequency SERS.

[0065] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A surface enhanced Raman detection substrate for low frequency Raman interference free signals, characterized in that, The surface-enhanced Raman scattering nanoparticles and the magnetic aggregation substrate, wherein the surface-enhanced Raman scattering nanoparticles are double-sphere structure nanoparticles composed of gold nanospheres and ferroferric oxide nanospheres; the magnetic aggregation substrate comprises monocrystalline silica flakes and neodymium-iron-boron magnets; and no low-frequency signal strong sodium citrate is added in the preparation process of the surface-enhanced Raman scattering nanoparticles.

2. The detection substrate of claim 1, wherein, In the surface-enhanced Raman scattering nanoparticles, the diameter of the gold nanospheres is 10-15 nm, and the diameter of the ferroferric oxide nanospheres is 15-20 nm; and the mass ratio of the gold nanospheres to the ferroferric oxide nanospheres is 1-3:

1.

3. The detection substrate of claim 1, wherein, The surface-enhanced Raman scattering nanoparticles have an ultraviolet-visible absorption peak of 515-520 nm, and can resonate with common laser with a wavelength of 514.5 nm. In the surface-enhanced Raman scattering nanoparticles, the optimal crystal face orientation of the ferroferric oxide is (111), and the optimal crystal face orientation of the gold is (100).

4. The detection substrate of claim 1, wherein, The surface-enhanced Raman scattering nanoparticles are modified by amino silane, which is obtained by the reaction of 3-aminopropyltrimethoxysilane and ammonia.

5. The detection substrate of claim 1, wherein, In the magnetic aggregation substrate, the monocrystalline silica flakes have no obvious low-frequency Raman signal, and the remanence of the neodymium-iron-boron magnets is greater than 11 kilogauss.

6. A method for surface enhanced Raman detection of an amino acid, comprising: The surface-enhanced Raman scattering nanoparticles as claimed in any one of claims 1-5 are mixed with a solution containing an amino acid to be detected, and then are placed in the magnetic aggregation substrate as claimed in any one of claims 1-5, so that an aggregation area of the surface-enhanced Raman scattering nanoparticles is formed on the surface of the monocrystalline silica, and the low-frequency Raman spectrum of the aggregation area is measured after drying.

7. The detection method of claim 6, wherein, The amino acid comprises one of cysteine, histidine, aspartic acid, arginine, phenylalanine, serine, tyrosine, alanine, methionine and isoleucine.

8. The detection method of claim 6, wherein, The solution containing the amino acid to be detected is a body fluid sample, which needs to be pretreated in the following manner to remove biological macromolecules: the body fluid sample is placed in a centrifugal ultrafiltration tube and centrifuged at 5000-10000 rpm for 2-10 minutes, and the liquid at the bottom of the ultrafiltration tube is taken as the sample to be detected; wherein the molecular cut-off of the centrifugal ultrafiltration tube is ≤ 3 kDa.

9. The detection method of claim 6, wherein, The surface-enhanced Raman scattering nanoparticles and the solution containing the amino acid to be detected are mixed in a volume ratio of 1:

10.

10. The detection method of claim 6, wherein, The measuring wave number of the low-frequency Raman spectrum is limited between 30 and 200 cm -1 The concentration of the amino acid with strong low-frequency Raman signal to be detected can be obtained by comparing the obtained low-frequency Raman spectrum with the low-frequency Raman spectrum of a standard amino acid sample, wherein the Raman laser wavelength matches the ultraviolet-visible absorption peak of the surface-enhanced Raman scattering nanoparticles.

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