Biomolecule low-frequency Raman signal detection method based on resonance Raman technology

Abstract

The invention belongs to the technical field of spectral analysis, and particularly relates to a method for enhancing low-frequency Raman signals of biomolecules by using a resonance Raman technology. Aiming at biomolecules with characteristic low-frequency signals, such as amino acids, neurotransmitters, lipids and the like, the invention establishes a systematic resonance enhancement detection method for the first time. Compared with an existing surface enhanced Raman technology, the scheme gets rid of dependence on a specific nano substrate, and universal detection of various biomolecules is realized by optimizing an excitation wavelength selection algorithm (such as a 1 / e intensity range criterion) and a substrate treatment process (such as a dry oxygen silicon oxide substrate). Experiments prove that the detection limit of the method on molecules such as histamine and dopamine is reduced by one order of magnitude compared with that of a conventional Raman technology.

Description

Technical Field

[0001] The present invention belongs to the technical field of spectral analysis, and in particular relates to a method for enhancing low-frequency Raman signals of biological molecules by utilizing resonance Raman technology. Background Art

[0002] Biomolecular detection technology is of great significance in a variety of fields, including medicine, biomedical research, food safety, environmental monitoring, and forensic medicine. This is particularly true for the diagnosis and monitoring of certain diseases. For example, histamine is a key mediator of allergic reactions, and measuring its levels can help diagnose allergic conditions such as urticaria, allergic rhinitis, and asthma. Dopamine is a crucial neurotransmitter, and abnormal levels of it are associated with diseases such as Parkinson's disease and schizophrenia. Timely testing can help understand the progression of the disease. High triglyceride levels are an independent risk factor for cardiovascular disease. Regular testing can help detect and intervene in hyperlipidemia early, reducing the risk of cardiovascular disease. Blood glucose levels are a key indicator for diagnosing diabetes and can also help monitor blood glucose control in diabetic patients and guide treatment adjustments. Liver and kidney diseases can affect serine metabolism, and measuring its levels can aid in the diagnosis of these diseases and monitor disease progression and treatment effectiveness. Low-density lipoprotein cholesterol is a major risk factor for atherosclerosis. Measuring its levels can assess the risk of atherosclerosis, providing an important basis for cardiovascular disease prevention.

[0003] Currently, the main detection technologies for biomolecules are: mass spectrometry, which has high sensitivity and high resolution, but the instrument cost is high and requires professional operation and data analysis skills; immunoassays, such as enzyme-linked immunosorbent assay (ELISA) and immunoblotting, are used to detect specific proteins or antigens and have high specificity and sensitivity, but usually require the preparation and use of antibodies, and the sample preparation is complex and costly; chromatography, including high-performance liquid chromatography (HPLC) and gas chromatography (GC), is used to separate and analyze complex biomolecule mixtures and has high resolution and quantitative analysis capabilities, but requires a long analysis time and a complex sample pre-treatment process.

[0004] Traditional Raman spectroscopy technology is difficult to detect signals in the low-frequency region (50-200cm-1) due to the weak Raman scattering signal and strong Rayleigh scattering background. Especially in the field of biomolecule detection, the Raman scattering signal is relatively weak and mixed with the signals of various biological substances, making it even more difficult to extract the signal of a specific biomolecule. Therefore, it is usually necessary to rely on the assistance of multiple optical and electrical technologies to obtain sufficient signal intensity. This is also the reason why current biomolecule research is mainly concentrated in the high-frequency region (generally >200cm-1). However, the relative vibration between groups in some biomolecules is relatively strong, resulting in their low-frequency Raman signals being much stronger than the high-frequency signals. This provides an important opportunity to detect characteristic biomolecules through low-frequency Raman signals.

[0005] Low-frequency Raman signals can reflect a mixture of intramolecular and intermolecular vibrational modes, thereby providing detailed information about the molecular structure and its environment, revealing the collective motion of biomacromolecules and the role of hydrogen bonds between biomolecules. The applicant's research has found that some biomolecules, such as amino acids, blood sugar, neurotransmitters (such as histamine and dopamine), cholesterol, triglycerides, etc., have significantly stronger signals in the low-frequency region than in the high-frequency region. By detecting the low-frequency signals of these biomolecules, the detection accuracy of these biomolecules in body fluids may be significantly improved. At present, relevant research on low-frequency signal detection is still relatively scarce.

[0006] Resonance Raman technology significantly enhances the Raman signal of a specific molecule by selecting an appropriate excitation light wavelength to match the wavelength of the target molecule's electronic transition. The advantages of this technology include: high sensitivity, capable of detecting low-concentration samples, and particularly suitable for studying biomacromolecules, trace substances, and other fields; good selectivity, as long as the frequency of the incident light resonates with the molecule's electronic transition, a significant resonance Raman signal will be generated. Therefore, it is possible to study the structure or functional groups of a specific molecule in a targeted manner; rich structural information, such as band position, intensity, and peak shape, are closely related to the molecule's electronic structure and vibrational coupling with surrounding molecules. This information can be used to infer structural features such as the molecule's concentration, chemical bond properties, molecular symmetry, and the environment in which it is located; background suppression, through the use of time-gating technology, can effectively remove the fluorescence signal background, thereby significantly enhancing the Raman signal.

[0007] Currently, surface-enhanced Raman technology is the primary method for detecting high-frequency Raman signals from biomolecules. However, this technology is limited by the types and mechanisms of surface-enhanced scattering substrates (including electromagnetic and chemical enhancement), resulting in limitations in the universal detection of a wide range of molecules. In particular, for some biomolecules with strong low-frequency Raman signals, existing research and development has not yet addressed resonance Raman enhancement techniques. Therefore, the present invention proposes a unique technical solution for effectively enhancing low-frequency Raman signals from biomolecules. Summary of the Invention

[0008] The present invention aims to solve the problem of low sensitivity in detecting low-frequency Raman signals of biomolecules in the prior art and provides a method for enhancing low-frequency Raman signals of biomolecules based on resonance Raman technology.

[0009] Specifically, the present invention provides a method for detecting low-frequency Raman signals of biomolecules based on resonance Raman technology, which comprises the following steps:

[0010] (1) Selecting an excitation wavelength that matches the electronic transition wavelength of the target biomolecule;

[0011] (2) drop-coating the target biomolecule solution on a substrate that is non-fluorescent and has no low-frequency Raman signal;

[0012] (3) The sample is excited with the selected excitation light wavelength, the low-frequency Raman signal is collected by a Raman spectrometer, and its signal intensity and spectral characteristics are recorded.

[0013] Preferably, the step of selecting the excitation light wavelength includes:

[0014] (1-1) Exciting the biomolecule to be tested with excitation light of any wavelength and detecting its photoluminescence (PL) spectrum;

[0015] (1-2) In the detected PL spectrum, monitoring the center position of the PL peak and the positions of multiple wavelengths before and after it (at least more than four wavelengths), measuring the corresponding photoexcitation PLE spectrum, and determining the maximum intensity PLE spectrum and its corresponding maximum intensity peak position;

[0016] (1-3) Using the peak position of the maximum intensity PLE spectrum as the wavelength of the excitation light, and measuring the corresponding PL spectrum again, obtain the PL spectrum with the maximum luminescence intensity and its most obvious peak position;

[0017] (1-4) A laser wavelength within the 1 / e intensity range before and after the central wavelength is selected as the Raman excitation light, where e is the natural logarithm, which is approximately 2.718.

[0018] Preferably, the substrate is single crystal silicon, single crystal 3C-SiC or single crystal silicon that has been subjected to dry oxygen oxidation treatment.

[0019] Preferably, the target biomolecule includes one of amino acids, glucose, neurotransmitters, cholesterol, triglycerides, and low-density lipoprotein cholesterol.

[0020] Preferably, the Raman spectrometer uses a laser wavelength of 532 nm, 633 nm, 785 nm or 1064 nm, or uses a tunable laser with a continuously adjustable excitation wavelength.

[0021] Preferably, the method further includes systematic processing of the collected Raman signals, including response correction of the Raman spectrometer under different excitation wavelengths, background subtraction of the spectrum, baseline correction, and spectrum normalization.

[0022] Preferably, the relative intensity of the low-frequency Raman signal can be enhanced by 5 to 20 times.

[0023] Preferably, in the sample preparation step, the concentration of the target biomolecule solution is such that a weak non-resonance Raman peak can be detected.

[0024] Preferably, the frequency range of the low-frequency Raman signal is 50-200 cm -1 .

[0025] Compared with the prior art, the present invention has the following advantages:

[0026] First, this invention establishes a systematic resonance-enhanced detection method for biomolecules with characteristic low-frequency signals, such as amino acids, neurotransmitters, and lipids. Compared to existing surface-enhanced Raman techniques, this approach eliminates the reliance on specific nanostructured substrates. By optimizing the excitation wavelength selection algorithm (such as the 1 / e intensity range criterion) and substrate processing techniques (such as dry oxygen-oxidized silicon substrates), it achieves universal detection of a wide range of biomolecules. Experiments have demonstrated that this method reduces the detection limit of molecules such as histamine and dopamine by an order of magnitude compared to conventional Raman techniques.

[0027] Secondly, by precisely matching the excitation light wavelength with the electronic transition characteristics of the target molecule, the present invention achieves the 50-200cm -1 The 5-20 times enhancement of low-frequency Raman signals solves the technical problem of weak low-frequency signals in traditional Raman technology and easy to be masked by Rayleigh scattering. This enhancement makes it possible to detect trace molecules (such as 10 -6 The sensitivity of mass spectrometry can reach or exceed that of existing mass spectrometry, while avoiding the high equipment cost and complicated sample pre-treatment process of mass spectrometry.

[0028] Finally, the present invention retains the characteristics of molecular vibrational spectroscopy and can provide detailed information about the molecular structure and its environment, which helps to conduct in-depth research on the chemical properties and biological functions of molecules, especially in terms of detecting concentration and molecular configuration changes, and can provide accurate predictions for the prevention and treatment of related biological molecules and diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 : Schematic diagram of the resonance Raman technology of the present invention, where the green arrow is the incident laser and the red arrow is the scattered light; the left side is ordinary Raman scattering; the right side is resonance Raman scattering.

[0030] Figure 2 : The present invention uses a xenon lamp with continuously adjustable wavelength as the excitation light source to detect the PL spectrum example of maximum intensity.

[0031] Figure 3 : Spectra of histamine in Application Example 1: a. PL spectrum of histamine, b. non-resonance Raman spectrum of histamine, c. resonance Raman spectrum of histamine.

[0032] Figure 4 : Spectra of dopamine in Application Example 2: a. PL spectrum of dopamine, b. non-resonance Raman spectrum of dopamine, c. resonance Raman spectrum of dopamine.

[0033] Figure 5: Spectra of serine in Application Example 3: a. PL spectrum of serine, b. non-resonance Raman spectrum of serine, c. resonance Raman spectrum of serine.

[0034] Figure 6 : Spectra of glucose in Application Example 4: a. PL spectrum of glucose, b. non-resonance Raman spectrum of glucose, c. resonance Raman spectrum of glucose.

[0035] Figure 7 : Spectra of triglycerides in Application Example 5: a. PL spectrum of triglycerides, b. non-resonance Raman spectrum of triglycerides, c. resonance Raman spectrum of triglycerides. DETAILED DESCRIPTION

[0036] The present invention selects the excitation light wavelength that matches the target molecule's electronic transition wavelength and utilizes the resonance effect to significantly enhance the low-frequency Raman signal. The principle is as follows: Figure 1 shown. Figure 1 In the figure, the left side shows normal Raman scattering, while the right side shows resonance Raman scattering. When the excitation wavelength matches the energy of the molecular electron transition, resonant absorption occurs, greatly enhancing the scattering signal. When processing fluorescence spectra with multiple wavelengths, it is particularly important to select the appropriate excitation wavelength based on the intensity of the fluorescence peak and the response sensitivity of the Raman spectrometer used at different wavelengths.

[0037] The specific steps are as follows:

[0038] The steps for selecting the excitation light wavelength are as follows:

[0039] (1) Photoluminescence (PL) spectrum measurement: First, the molecule to be measured is excited by excitation light of any wavelength, and its PL spectrum is detected, which is usually called fluorescence spectrum.

[0040] (2) Photoinduced excitation (PLE) spectrum measurement: In the detected PL spectrum, the center position of the PL peak (i.e., the maximum wavelength) and the four wavelength positions before and after it are monitored. By monitoring these positions and measuring the corresponding PLE spectra, five different PLE spectra can be obtained. The intensities of these spectra are compared to determine the PLE spectrum with the maximum intensity and its corresponding maximum intensity peak position.

[0041] (3) Select the excitation light wavelength: Use the peak position of the maximum intensity PLE spectrum as the wavelength of the excitation light, and measure the corresponding PL spectrum again to obtain the PL spectrum with maximum luminescence intensity and its most obvious peak position.

[0042] (4) Selection of Raman excitation light: For Raman excitation light, a laser wavelength within the 1 / e intensity range before and after the central wavelength (most visible peak position) is selected for excitation.

[0043] like Figure 2As shown, taking histamine as an example, a xenon lamp with continuously adjustable wavelength is used as the excitation light source to detect the PL spectrum with the maximum intensity. a. Use any excitation wavelength (450nm line) to detect and obtain a corresponding PL spectrum, whose strongest peak is located at 570nm. b. Monitor at the strongest PL peak of 570nm, and detect a PLE peak, whose maximum intensity is located at 500nm. c. Use 5 wavelengths before and after 500nm as excitation light, and detect and obtain 5 corresponding PL spectra, and the PL peak of intensity is located at 600nm. d. Monitor the PLE spectrum at 5 wavelengths before and after the strongest 600nm PL peak. Here we see that the strongest PLE peak is located at 520nm. Through such detection steps, the center position of the corresponding strongest PL spectrum can be obtained, as shown in Figure 3-7 shown.

[0044] Through the above steps, the electronic transition wavelength of biological molecules (such as histamine, serine, blood glucose, etc.) can be determined, thereby selecting a suitable excitation light wavelength.

[0045] Biomolecule screening: To significantly improve the sensitivity of detecting target molecules in a variety of biomolecule mixtures, it is necessary to clearly identify biomolecules whose low-frequency Raman signal intensity exceeds half of their high-frequency Raman signal intensity. To achieve this, Raman detection requires selecting excitation light that is not within the 1 / e range of the maximum PL peak intensity to obtain non-resonant Raman spectra. By analyzing the Raman intensity in the low-frequency region, it is possible to determine which biomolecules have strong low-frequency signals, thereby identifying the target biomolecules to be detected.

[0046] Substrate selection: The target molecule is drop-coated in the form of a solution on a substrate that is non-fluorescent and has no low-frequency Raman signal. We mainly consider three substrate materials: single crystal silicon, single crystal 3C-SiC and single crystal silicon treated with dry oxygen oxidation, and their crystal plane orientation is not limited. Single crystal silicon and single crystal 3C-SiC are both non-indirect band gap semiconductors with body band gaps of 1.12eV and 2.24eV, respectively. At low temperatures (less than 120K), they can only emit very weak infrared light and yellow light, and no light is emitted at room temperature. For dry oxygen oxidized silicon substrates, it is necessary to first detect whether the silicon oxide formed by dry oxygen oxidation on the surface is stoichiometric SiO2. To this end, it is necessary to first use infrared spectroscopy to detect the infrared vibration spectrum of silicon oxide to confirm whether it has the stretching vibration mode of the Si-O-Si bond, and its characteristic peak is located at the standard 1076cm -1 If it deviates from this position, the substrate is not suitable for use because the silicon oxide film may contain defect structures such as oxygen vacancies and oxygen interstitials. These defects will lead to the appearance of room temperature photoluminescence spectra, thereby interfering with the accurate judgment of the fluorescence spectrum of the molecules to be measured.

[0047] Sample Preparation: Prepare a glucose-water solution containing the desired molecule at a concentration sufficient to detect a weak non-resonant Raman peak. Apply the solution to any selected substrate. If necessary, dry the sample to ensure uniform distribution of the molecule across the substrate surface.

[0048] Raman signal acquisition: The sample is excited with a laser wavelength that matches the target molecule's electronic transition wavelength (i.e., a wavelength within the 1 / e range of the maximum intensity in the PL spectrum). A Raman spectrometer collects low-frequency Raman signals and records their signal intensity and spectral characteristics. As a general choice, the four most commonly used commercial laser wavelengths are 532 nm, 633 nm, 785 nm, and 1064 nm. These laser wavelengths cover the visible to near-infrared range and are suitable for resonance Raman measurements of the fluorescence properties of various molecules. Alternatively, a tunable laser with a continuously adjustable excitation wavelength can be used to more precisely match the molecule's electronic transitions and achieve stronger resonance Raman enhancement. For most biomolecules, their fluorescence emission peaks typically fall between 400 and 800 nm. Therefore, using only two laser wavelengths, 532 nm and 785 nm, can provide a preliminary assessment of the presence of resonance enhancement, effectively screening for target molecules with significant Raman responses.

[0049] Data Analysis: The collected Raman signals are systematically processed, including calibration of the Raman spectrometer's response at different excitation wavelengths, background subtraction of the spectra, baseline correction, and spectral normalization. Specifically, the low-frequency Raman region is analyzed, serving as a characteristic baseline spectral region for the molecule being detected. The integrated area is calculated to determine whether the low-frequency signal is sufficiently intense, thereby assessing its feasibility as a target for resonance Raman detection. Subsequently, by comparing the Raman signal intensities before and after resonance enhancement, the enhancement factor is determined and the significance and practicality of the resonance enhancement effect are evaluated.

[0050] Application Example 1:

[0051] This application example uses resonance Raman technology to detect the low-frequency Raman signal of histamine.

[0052] 1. Use a 532nm laser as the excitation light source to detect the PL spectrum of histamine and determine the electronic transition wavelength range of the target molecule. According to the determined electronic transition wavelength, select a laser wavelength that matches it. The results show that the 532nm light source can resonate within the 1 / e range of the histamine fluorescence intensity; the 785nm light source is not within the fluorescence range and does not resonate (such as Figure 3 a).

[0053] 2. Apply 20 μL of 1 M histamine solution to a dry oxygen-oxidized silica substrate (SiO2 / Si) that is devoid of fluorescence and low-frequency Raman signals. Dry the sample to ensure that the molecules are evenly distributed on the substrate surface.

[0054] 3. Non-resonant Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 785nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 3 b. Measure each sample at least five times at different points to improve data reliability.

[0055] 4. Resonance Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 532nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 3 c. Measure each sample at least five times at different points to improve data reliability.

[0056] 5. Comparing the signal strength before and after resonance enhancement, both high and low frequency signals are significantly enhanced, but the low frequency enhancement is more obvious. After analysis and calculation, the enhancement multiple is about 7 times.

[0057] Application Example 2:

[0058] This application example uses resonance Raman technology to detect the low-frequency Raman signal of dopamine.

[0059] 1. Use a 532nm laser as the excitation light source to detect the PL spectrum of dopamine and determine the electronic transition wavelength range of the target molecule. According to the determined electronic transition wavelength, select a laser wavelength that matches it. The results show that the 532nm light source can resonate within the 1 / e range of the histamine fluorescence intensity; the 785nm light source is not within the fluorescence range and does not resonate (such as Figure 4 a).

[0060] 2. Drop-coat 20 μL of a 1 M dopamine solution onto a dry oxygen-oxidized silica substrate (SiO2 / Si) that is devoid of fluorescence and low-frequency Raman signals. Dry the sample to ensure uniform distribution of the molecules on the substrate surface.

[0061] 3. Non-resonant Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 785nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 4 b. Measure each sample at least five times at different points to improve data reliability.

[0062] 4. Resonance Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 532nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 4 c. Measure each sample at least five times at different points to improve data reliability.

[0063] 5. Comparing the signal strength before and after resonance enhancement, both high and low frequency signals are significantly enhanced, but the low frequency enhancement is more obvious. After analysis and calculation, the enhancement multiple is about 20 times.

[0064] Application Example 3:

[0065] This application example uses resonance Raman technology to detect the low-frequency Raman signal of serine.

[0066] 1. Use a 532nm laser as the excitation light source to detect the PL spectrum of serine and determine the electronic transition wavelength range of the target molecule. According to the determined electronic transition wavelength, select a laser wavelength that matches it. The results show that the 532nm light source can resonate within the 1 / e range of the histamine fluorescence intensity; the 785nm light source is not within the fluorescence range and does not resonate (such as Figure 5 a).

[0067] 2. Apply 20 μL of a 1 M serine solution to a dry oxygen-oxidized silica substrate (SiO2 / Si) that is devoid of fluorescence and low-frequency Raman signals. Dry the sample to ensure uniform distribution of the molecules on the substrate surface.

[0068] 3. Traditional Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 785nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 5 b. Measure each sample at least five times at different points to improve data reliability.

[0069] 4. Resonance Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 532nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 5 c. Measure each sample at least five times at different points to improve data reliability.

[0070] 5. Comparing the signal strength before and after resonance enhancement, both high and low frequency signals are significantly enhanced, but the low frequency enhancement is more obvious. After analysis and calculation, the enhancement multiple is about 10 times.

[0071] Application Example 4:

[0072] This application example uses resonance Raman technology to detect the low-frequency Raman signal of glucose.

[0073] 1. Use a 532nm laser as the excitation light source to detect the PL spectrum of glucose and determine the electronic transition wavelength range of the target molecule. According to the determined electronic transition wavelength, select a laser wavelength that matches it. The results show that the 532nm light source can resonate within the 1 / e range of the histamine fluorescence intensity; the 785nm light source is not within the fluorescence range and does not resonate (such as Figure 6 a).

[0074] 2. Apply 20 μL of 1 M glucose solution to a dry oxygen-oxidized silica substrate (SiO2 / Si) that is devoid of fluorescence and low-frequency Raman signals. Dry the sample to ensure uniform distribution of the molecules on the substrate surface.

[0075] 3. Traditional Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 785nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 6 b. Measure each sample at least five times at different points to improve data reliability.

[0076] 4. Resonance Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 532nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 6 c. Measure each sample at least five times at different points to improve data reliability.

[0077] 5. Comparing the signal strength before and after resonance enhancement, both high and low frequency signals are significantly enhanced, but the low frequency enhancement is more obvious. After analysis and calculation, the enhancement multiple is about 5 times.

[0078] Application Example 5:

[0079] This application example uses resonance Raman technology to detect the low-frequency Raman signal of triglycerides.

[0080] 1. Use a 532nm laser as the excitation light source to detect the PL spectrum of triglycerides and determine the electronic transition wavelength range of the target molecule. According to the determined electronic transition wavelength, select a laser wavelength that matches it. The results show that the 532nm light source can resonate within the 1 / e range of the histamine fluorescence intensity; the 785nm light source is not within the fluorescence range and does not resonate (such as Figure 7 a).

[0081] 2. Apply 20 μL of a 1 M triglyceride solution to a dry oxygen-oxidized silica substrate (SiO2 / Si) that is devoid of fluorescence and low-frequency Raman signals. Dry the sample to ensure uniform distribution of the molecules on the substrate surface.

[0082] 3. Traditional Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 785nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 7 b. Measure each sample at least five times at different points to improve data reliability.

[0083] 4. Resonance Raman signal acquisition. Place the prepared sample on the sample stage of the Raman spectrometer. Adjust the laser wavelength to 532nm, set the laser power to 10mW, and the integration time to 20 seconds. Collect the Raman spectrum of the sample and record the signals in the low-frequency region and the high-frequency region (50-1500cm -1 ),like Figure 7 c. Measure each sample at least five times at different points to improve data reliability.

[0084] 5. Comparing the signal strength before and after resonance enhancement, both high and low frequency signals are significantly enhanced, but the low frequency peak is more obviously enhanced. After analysis and calculation, the enhancement factor is about 10 times.

Claims

1. A method for detecting low-frequency Raman signals of biomolecules based on resonance Raman technology, characterized in that: The following steps are involved: (1) Selecting an excitation wavelength that matches the electronic transition wavelength of the target biomolecule; (2) drop-coating the target biomolecule solution on a substrate that is non-fluorescent and has no low-frequency Raman signal; (3) The sample is excited with the selected excitation light wavelength, the low-frequency Raman signal is collected by a Raman spectrometer, and its signal intensity and spectral characteristics are recorded.

2. The detection method according to claim 1, wherein The step of selecting the excitation light wavelength comprises: (1-1) Exciting the biomolecule to be tested with excitation light of any wavelength and detecting its photoluminescence (PL) spectrum; (1-2) In the detected PL spectrum, the center position of the PL peak and the positions of multiple wavelengths before and after it are monitored, the corresponding photoexcitation PLE spectrum is measured, and the maximum intensity PLE spectrum and its corresponding maximum intensity peak position are determined; (1-3) Using the peak position of the maximum intensity PLE spectrum as the wavelength of the excitation light, and measuring the corresponding PL spectrum again, obtain the PL spectrum with the maximum luminescence intensity and its most obvious peak position; (1-4) A laser wavelength within the 1 / e intensity range before and after the center wavelength of the PL spectrum is selected as the Raman excitation light, where e is the natural logarithm.

3. The detection method according to claim 1, wherein The substrate is single crystal silicon, single crystal 3C-SiC or single crystal silicon that has been subjected to dry oxygen oxidation treatment.

4. The detection method according to claim 1, wherein The target biological molecule includes one of amino acids, glucose, neurotransmitters, cholesterol, triglycerides, and low-density lipoprotein cholesterol.

5. The detection method according to claim 1, wherein The Raman spectrometer uses a laser wavelength of 532 nm, 633 nm, 785 nm or 1064 nm, or uses a tunable laser with a continuously adjustable excitation wavelength.

6. The detection method according to claim 1, characterized in that It also includes systematic processing of the collected Raman signals, including response correction of the Raman spectrometer at different excitation wavelengths, background subtraction of the spectrum, baseline correction, and spectral normalization.

7. The detection method according to claim 1, characterized in that The relative intensity of the low-frequency Raman signal can be enhanced by 5 to 20 times.

8. The detection method according to claim 1, wherein In the sample preparation step, the concentration of the target biomolecule solution is a concentration at which a weak non-resonance Raman peak can be detected.

9. The detection method according to claim 1, wherein The frequency range of the low-frequency Raman signal is 50-200 cm -1 .

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