Neurotransmitter mass spectrometry analysis platform based on in-source light derivatization and application

Abstract

The invention discloses a neurotransmitter mass spectrum analysis platform based on in-source light derivatization, the platform comprises a 2-nitrobenzaldehyde photoreactive reagent and an inorganic nano matrix, the reagent and a neurotransmitter are subjected to Schiff alkali condensation reaction through mass spectrum in-source laser excitation, the matrix enhances electron transfer through a photon-generated carrier, and the fluorescence intensity of the neurotransmitter is improved. The platform is suitable for detection of neurotransmitters in cerebrospinal fluid, tears and other samples, can be applied to neurotransmitter metabonomics research, and especially can be used for analyzing smog disease patient samples in different cognitive states, screening different neurotransmitters and metabolites, and detecting the neurotransmitters and the metabolites. It is found that the maximum derivatization efficiency of metabolites related to the development of the vascular cognitive impairment can reach 99.9%, the maximum detection signal is enhanced by 10%, the reaction is in the nanosecond level, the single sample dosage is 1 microliter, the detection time is smaller than or equal to 5 seconds, the variable coefficient is smaller than or equal to 6%, and support is provided for mechanism research, early diagnosis and intervention of the vascular cognitive impairment.

Description

Technical Field

[0001] This invention relates to the field of mass spectrometry analysis technology, specifically to the mass spectrometry detection and metabolomics research of neurotransmitters, and particularly to a source-derived phototransmitter mass spectrometry analysis platform and its application. Background Technology

[0002] Vascular cognitive impairment (VCI) is the second most common type of dementia after Alzheimer's disease, with a complex pathogenesis and difficult early diagnosis. Studies have shown that chronic cerebral hypoperfusion and blood-brain barrier dysfunction can lead to metabolic imbalances in neurons and glial cells, thereby affecting cognitive function. However, our systematic understanding of neurotransmitter metabolic disorders in VCI remains insufficient. Moyamoya disease (MMD), due to its characteristics of chronic intracranial arterial stenosis and hypoperfusion, shares a similar pathological process with VCI, making it an ideal model for VCI research. In-depth understanding of the changes in neurotransmitter-related metabolites during VCI progression is crucial for early diagnosis and intervention; however, research in this area is limited by the lack of high-throughput, low-sample-size, and precisely comprehensive neurotransmitter metabolomics detection tools.

[0003] Mass spectrometry, with its advantages of high sensitivity and high resolution, has become a core method in metabolomics research. However, neurotransmitters, due to their low concentration and high polarity, suffer from low ionization efficiency and limited detection sensitivity in conventional mass spectrometry. While liquid chromatography-tandem mass spectrometry (LC-MS / MS) can enhance sensitivity by combining chemical derivatization, it suffers from problems such as complex pretreatment, long reaction time, and large sample consumption (≥50μL), making it unsuitable for rapid analysis of large samples. Matrix-assisted laser desorption / ionization mass spectrometry (MALDI-MS), while offering advantages such as small sample loading (approximately 1μL) and fast analysis speed (approximately 5s / sample), suffers from limitations such as low derivatization efficiency, high background noise, and poor reproducibility due to its traditional derivatization method which relies on reagent spraying and long incubation time (0.5-48 hours). Furthermore, existing photoderivatization reagents rely on organic matrices such as α-cyanocinonic acid, resulting in low labeling efficiency (less than 81%), which cannot meet the needs of precise neurotransmitter analysis.

[0004] Therefore, there is an urgent need to develop a mass spectrometry analysis platform with high efficiency in derivatization, low sample volume, rapid detection and good reproducibility, so as to adapt to a variety of biological samples, realize sensitive detection of neurotransmitters and screening of metabolite markers, and provide support for research on vascular cognitive impairment. Summary of the Invention

[0005] In view of the above-mentioned deficiencies of the prior art, the present invention will at least solve the following technical problems: 1) Due to their low content and high polarity, neurotransmitters suffer from low ionization efficiency and poor detection sensitivity in mass spectrometry analysis. Existing derivatization reagents have insufficient labeling efficiency (less than 81%), which makes it difficult to meet the needs of accurate analysis. 2) Liquid chromatography-tandem mass spectrometry (LC-MS / MS) combined with chemical derivatization involves complex pretreatment steps, long reaction times, and high sample consumption (≥50μL), making it unsuitable for high-throughput screening; the derivatization process of traditional matrix-assisted laser desorption / ionization mass spectrometry (MALDI-MS) relies on reagent spraying and long incubation (0.5-48 hours), which has limitations such as low derivatization efficiency, high background noise, and poor repeatability, and cannot achieve efficient derivatization and high-sensitivity detection; 3) In vascular cognitive impairment (VCI) research, there is a lack of high-throughput, low-sample-size detection tools that can accurately cover the neurotransmitter metabolome, making it difficult to systematically reveal the role of neurotransmitter metabolic disorders in VCI progression.

[0006] To achieve the above objectives, this invention discloses a mass spectrometry in-source photo-derivatization (MSIPD) platform for neurotransmitter analysis, comprising photoreactive reagents and an inorganic nanomatrix with photocatalytic properties; The photoreactive reagent is a 2-nitrobenzaldehyde compound, and the inorganic nanomatrix is ​​inorganic nanoparticles; The platform uses laser excitation within a mass spectrometry source to induce a Schiff base condensation reaction between the photoreactive reagent and the neurotransmitter. The inorganic nanomatrix enhances the electron transfer rate through photogenerated charge carriers. The two work synergistically to facilitate the derivatization and mass spectrometry detection of the neurotransmitter. Furthermore, the 2-nitrobenzaldehyde compound is 5-methoxy-2-nitrobenzaldehyde; Furthermore, the inorganic nanoparticles are Ti Nanoparticles Furthermore, the neurotransmitter includes at least one of dopamine, γ-aminobutyric acid, norepinephrine, 5-hydroxytryptamine, 3-methoxytyramine, and histamine; Furthermore, the solution of the photoreactive reagent is prepared by dissolving 5-methoxy-2-nitrobenzaldehyde in a mixture of acetonitrile, ethanol and water, wherein the volume ratio of acetonitrile, ethanol and water is 84:13:3, and the concentration of 5-methoxy-2-nitrobenzaldehyde in the mixture is 10 mg / mL. Furthermore, the derivatization reaction is at the nanosecond level, the single sample detection time does not exceed 5 seconds, the detection coefficient of variation is ≤6%, and the single sample volume is 1μL; Furthermore, the biological samples that the platform is compatible with include cerebrospinal fluid and tears; This invention also discloses an application of a neurotransmitter mass spectrometry analysis platform based on in-source photoderivation, including using the platform to perform in-source photoderivation processing and MALDI-MS detection on neurotransmitters in cerebrospinal fluid or tear fluid samples to achieve qualitative analysis of the neurotransmitters; Furthermore, the method includes using the platform to perform on-source photoderivative processing and MALDI-MS detection on neurotransmitters in samples from patients with Moyamoya disease who have no cognitive impairment, mild cognitive impairment, and severe cognitive impairment, and using qualitative analysis to screen for neurotransmitters and metabolites that differ among patients with different cognitive states.

[0007] Furthermore, it includes the following steps: S1: Collect cerebrospinal fluid samples from patients with Moyamoya disease who have no cognitive impairment, mild cognitive impairment, or severe cognitive impairment. Store the samples at -80°C and avoid repeated freeze-thaw cycles. S2: The platform is used to derivatize and detect neurotransmitters in the sample using MALDI-MS, and mass spectrometry data in the range of m / z 80–1000 are collected. S3: Perform multivariate statistical analysis on the collected mass spectrometry data to screen for neurotransmitters and metabolites that show significant differences among patients with no cognitive impairment, mild cognitive impairment, and severe cognitive impairment.

[0008] Compared with the prior art, the above-described technical solutions conceived in this invention have at least the following beneficial effects: 1) Improved derivatization efficiency and detection sensitivity: Through the synergistic effect of photoreactive reagents (2-nitrobenzaldehyde compounds) and photocatalytic inorganic nanomatrix, the derivatization efficiency of common neurotransmitters can reach up to 99.9%, significantly improving the detectability of low-abundance neurotransmitters; at the same time, it significantly enhances the detection signal of neurotransmitters, up to 10², solving the problems of low ionization efficiency and poor detection sensitivity caused by low content and strong polarity of neurotransmitters; 2) Shorten the analysis cycle and improve detection efficiency and repeatability: The derivatization reaction is a nanosecond-level instantaneous reaction, which does not require long incubation or complex pretreatment steps. The detection time for a single sample is no more than 5 seconds, and the volume of a single sample is only 1μL, which is suitable for large-scale population studies. The coefficient of variation (CV value) of the platform detection is ≤6%, which meets the stability requirements of clinical research and overcomes the shortcomings of traditional liquid chromatography-tandem mass spectrometry (LC-MS / MS) with its complex pretreatment and large sample consumption, as well as the time-consuming derivatization and poor repeatability of conventional matrix-assisted laser desorption / ionization mass spectrometry (MALDI-MS). 3) Enhance the platform's versatility and application value: It is compatible with multiple types of biological samples (such as cerebrospinal fluid, tears, etc.), and has high platform versatility and scalability; when applied to the study of moyamoya disease-related vascular cognitive impairment (VCI), it can screen out neurotransmitters and metabolites related to VCI progression, providing support for the study of VCI mechanisms, early diagnosis and intervention, and filling the gap in the current VCI research of lacking high-throughput, low-sample-volume neurotransmitter metabolomics detection tools. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of the workflow of the MSIPD platform of the present invention; Figure 2 This is a schematic diagram illustrating the detection results of six neurotransmitter standards using the MSIPD platform of the present invention. Figure 2 A is a schematic diagram comparing the mass spectrometry signal intensity before and after derivatization. Figure 2 B is a schematic diagram of the derivatization efficiency of each neurotransmitter; Figure 3 This is a representative property spectrum of neurotransmitters detected in cerebrospinal fluid samples using the MSIPD platform of the present invention; Figure 4 This is a schematic diagram illustrating the cerebrospinal fluid metabolomics analysis results of three groups of patients with moyamoya disease in different cognitive states using the MSIPD platform of the present invention. Figure 4 A represents the ROC curves for pairwise differentiation of the three patient groups. Figure 4 B shows the expression trends of differentially expressed neurotransmitters and metabolites in the three groups of patients. Detailed Implementation

[0010] The following description, with reference to the accompanying drawings, illustrates several preferred embodiments of the present invention to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0011] This invention discloses a source-based photoderivatization neurotransmitter mass spectrometry analysis platform. The platform includes a photoreactive reagent and an inorganic nanomatrix with photocatalytic properties. The photoreactive reagent is a 2-nitrobenzaldehyde compound, and the inorganic nanomatrix is ​​inorganic nanoparticles. The platform uses source-based laser excitation to induce a Schiff base condensation reaction between the photoreactive reagent and the neurotransmitter. Simultaneously, the inorganic nanomatrix enhances the electron transfer rate through photogenerated charge carriers. The two work synergistically to promote the derivatization and mass spectrometry detection of the neurotransmitter.

[0012] The embodiments of this application will be described in detail below.

[0013] Example 1

[0014] This embodiment aims to construct a mass spectrometry-based in-source photoderivatization (MSIPD) platform for sensitive detection of neurotransmitters. The specific steps are as follows: Step 1: Prepare photoderivatization reagent solution Dissolve 5-methoxy-2-nitrobenzaldehyde (5-OCH3-NBA, a type of 2-nitrobenzaldehyde photoreactive reagent) in a mixture of acetonitrile, ethanol and water (volume ratio of the three is 84:13:3) to prepare a solution with a concentration of 10 mg / mL. Store in the dark for later use.

[0015] Step 2: Preparation of inorganic photocatalytic matrix materials

[0016] Take Ti Nanoparticles (a type of inorganic nanomatrix) were dissolved in deionized water to prepare a solution with a concentration of 1 mg / mL, and ultrasonically dispersed for 15 minutes to ensure uniform dispersion of the particles.

[0017] Step 3: Sample mixing

[0018] Mix the photoderivative reagent solution prepared in step 1 with neurotransmitter standards (or biological samples such as cerebrospinal fluid and tears) at a volume ratio of 1:1 to obtain a mixture.

[0019] Step 4: Spotting Processing

[0020] Take 1 μL of the above mixture and spot it onto a 384-polished matrix-assisted laser desorption / ionization mass spectrometry (MALDI-MS) target plate. Place it in a vacuum desiccator to dry in the dark to remove the solvent.

[0021] Step 5: Matrix Loading

[0022] Add 1 μL of the Ti solution prepared in step 2 to the dried sample spot. The nanoparticle solution was dried again under vacuum in the dark to complete sample preparation.

[0023] Step 6: Mass spectrometry detection

[0024] The prepared target plate was placed in a MALDI-MS instrument. The instrument's built-in laser excitation caused the photoreactive reagents within the sample to undergo a Schiff base condensation reaction with the neurotransmitters, while Ti... Nanomatrices enhance electron transfer through photogenerated charge carriers, synergistically enabling derivatization and detection.

[0025] The workflow of the MSIPD platform constructed in this embodiment is as follows: Figure 1 As shown, the core technology lies in achieving instant derivatization through laser excitation within a mass spectrometry source, without the need for additional incubation steps.

[0026] Example 2

[0027] This embodiment aims to verify the detection performance (derivation efficiency and signal strength) of the MSIPD platform for common neurotransmitters. The specific steps are as follows: Step 1: Prepare neurotransmitter standards Aqueous solutions of dopamine (DA), γ-aminobutyric acid (GABA), norepinephrine (NE), 5-hydroxytryptamine (5-HT), 3-methoxytyramine (3-MT), and histamine (Histm) were prepared at a concentration of 1 mg / mL and used as the detection targets.

[0028] Step 2: Sample processing

[0029] Following steps 3-5 of Example 1, the above six neurotransmitter standards were mixed, spotted, and subjected to matrix loading treatment.

[0030] Step 3: Mass spectrometry detection and result analysis

[0031] The mass spectrometry signal intensity and derivatization efficiency of each neurotransmitter were analyzed using a Bruker Autoflex MALDI-TOF MS instrument.

[0032] The MSIPD platform's detection results for the above-mentioned common neurotransmitters are as follows: Figure 2 As shown, Figure 2 A shows the comparison of mass spectrometry signal intensity before and after derivatization. It can be seen that the signals of each neurotransmitter are significantly enhanced after derivatization (up to 10²). Figure 2 B represents the derivation efficiency of each neurotransmitter, all of which are above 93%, with the highest reaching 99.9%, verifying the platform's efficient derivation capability for neurotransmitters.

[0033] Example 3

[0034] This embodiment aims to verify the detection effect of the MSIPD platform on neurotransmitters in actual biological samples. Taking cerebrospinal fluid and tear fluid samples as examples, the specific steps are as follows: Step 1: Sample Collection Collect cerebrospinal fluid and tear samples and store them at -80°C to avoid repeated freeze-thaw cycles.

[0035] Step 2: Sample processing

[0036] Following steps 3-5 of Example 1, the cerebrospinal fluid and tear fluid samples were mixed (with photoderivatization reagent), spotted, and subjected to matrix loading treatment.

[0037] Step 3: Mass spectrometry detection and qualitative analysis

[0038] Mass spectrometry data were collected using a MALDI-MS instrument, and characteristic peak signals of neurotransmitters were extracted and qualitatively analyzed.

[0039] Representative spectral data of cerebrospinal fluid samples are shown below. Figure 3 As shown, the underived cerebrospinal fluid sample showed no obvious neurotransmitter signals (signal-to-noise ratio S / N < 3); the sample processed by the MSIPD platform showed characteristic peaks of neurotransmitters such as 3-methoxytyramine (3-MT), norepinephrine (NE), 5-hydroxytryptamine (5-HT), and dopamine (DA) (signal-to-noise ratio ≥ 20), verifying the platform's sensitive detection capability of neurotransmitters in biological samples.

[0040] Example 4

[0041] This embodiment aims to use the MSIPD platform to analyze the differences in neurotransmitters and metabolites in the cerebrospinal fluid of patients with moyamoya disease in different cognitive states, providing support for VCI research. The specific steps are as follows: Step 1: Sample Collection Cerebrospinal fluid samples were collected from patients with Moyamoya disease and divided into three groups according to their cognitive status: no cognitive impairment (NCI), mild cognitive impairment (MCI), and severe cognitive impairment (SCI), with ≥30 samples in each group; samples were stored at -80℃ to avoid repeated freeze-thaw cycles.

[0042] Step 2: Sample processing and testing

[0043] Following steps 3-6 of Example 1, the three groups of samples were processed and subjected to MALDI-MS detection. The BrukerAutoflex MALDI-TOF MS instrument was used to detect the samples, and mass spectrometry data in the range of m / z 80–1000 were collected. Characteristic peak signals related to neurotransmitters and their metabolites were extracted to construct a cerebrospinal fluid metabolic fingerprint.

[0044] Step 3: Data Analysis

[0045] Mass spectrometry data were imported into a logistic regression model, and combined with multivariate statistical analysis, to screen for neurotransmitters and metabolites that showed significant differences among the three groups.

[0046] The above analysis results are as follows Figure 4 As shown, where Figure 4 A represents the ROC curves that differentiate between the three groups of patients, with the highest differentiation power between the group without cognitive impairment and the group with severe cognitive impairment (AUC=0.949). Figure 4 B shows the expression trends of differentially expressed neurotransmitters and metabolites in the three groups, validating the application value of the platform in VCI-related metabolomics research.

[0047] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A neurotransmitter mass spectrometry analysis platform based on source photoderivation, characterized in that, Including photoreactive reagents and inorganic nanomatrices with photocatalytic properties; The photoreactive reagent is a 2-nitrobenzaldehyde compound, and the inorganic nanomatrix is ​​inorganic nanoparticles; The platform uses laser excitation within a mass spectrometry source to induce a Schiff base condensation reaction between the photoreactive reagent and the neurotransmitter. The inorganic nanomatrix enhances the electron transfer rate through photogenerated charge carriers. The two work synergistically to facilitate the derivatization and mass spectrometry detection of the neurotransmitter.

2. The neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 1, characterized in that, The 2-nitrobenzaldehyde compound is 5-methoxy-2-nitrobenzaldehyde.

3. The neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 1, characterized in that, The inorganic nanoparticles are Ti Nanoparticles.

4. The neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 1, characterized in that, The neurotransmitters include at least one of dopamine, γ-aminobutyric acid, norepinephrine, 5-hydroxytryptamine, 3-methoxytyramine, and histamine.

5. The neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 1, characterized in that, The photoreactive reagent solution is prepared by dissolving 5-methoxy-2-nitrobenzaldehyde in a mixture of acetonitrile, ethanol and water, wherein the volume ratio of acetonitrile, ethanol and water is 84:13:3, and the concentration of 5-methoxy-2-nitrobenzaldehyde in the mixture is 10 mg / mL.

6. The neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 1, characterized in that, The derivatization reaction is at the nanosecond level, the single sample detection time is no more than 5 seconds, the coefficient of variation is ≤6%, and the single sample volume is 1μL.

7. The neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 1, characterized in that, The biological samples that the platform is compatible with include cerebrospinal fluid and tears.

8. An application of the neurotransmitter mass spectrometry analysis platform based on source photoderivation as described in any one of claims 1-7, characterized in that, This includes using the platform to perform on-source photoderivative processing and MALDI-MS detection of neurotransmitters in cerebrospinal fluid or tear fluid samples, thereby achieving qualitative analysis of the neurotransmitters.

9. The application of the neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 8, characterized in that, This includes using the platform to perform on-source photoderivative processing and MALDI-MS detection of neurotransmitters in samples from patients with Moyamoya disease who have no cognitive impairment, mild cognitive impairment, and severe cognitive impairment, and using qualitative analysis to screen for neurotransmitters and metabolites that differ among patients with the above different cognitive states.

10. The application of the neurotransmitter mass spectrometry analysis platform based on source photoderivation according to claim 9, characterized in that, Includes the following steps: S1: Collect cerebrospinal fluid samples from patients with Moyamoya disease who have no cognitive impairment, mild cognitive impairment, or severe cognitive impairment. Store the samples at -80°C and avoid repeated freeze-thaw cycles. S2: The platform is used to derivatize and detect neurotransmitters in the sample using MALDI-MS, and mass spectrometry data in the range of m / z 80–1000 are collected. S3: Perform multivariate statistical analysis on the collected mass spectrometry data to screen for neurotransmitters and metabolites that show significant differences among patients with no cognitive impairment, mild cognitive impairment, and severe cognitive impairment.

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