Identification method of benzotriazole ultraviolet stabilizer pollutants

Abstract

The invention discloses an identification method of benzotriazole ultraviolet stabilizer pollutants. The identification method comprises the following steps: (1) constructing a suspected target database of the benzotriazole ultraviolet stabilizer pollutants; (2) performing liquid chromatography-mass spectrometry analysis on the environmental sample to be detected, and obtaining data dependent acquisition data of the environmental sample to be detected in a data dependent acquisition mode; (3) performing similarity analysis on the data-dependent acquired data based on information of compounds in the suspected target database, and determining structures of suspected compounds similar to the compounds in the suspected target database; (4) screening out candidate compounds similar to mass spectrum information of the known benzotriazole pollutants by means of a molecular network; and analyzing the chromatographic information and the mass spectrum information related to the candidate compound in the data dependent acquisition data, and determining the structure of the candidate compound. According to the invention, synchronous identification and identification of a target compound, a suspicious compound and a completely unknown compound can be realized.

Description

Technical Field

[0001] This invention relates to the fields of environmental analytical chemistry and pollutant monitoring technology, and in particular to a method for identifying benzotriazole ultraviolet stabilizer pollutants. Background Technology

[0002] UV stabilizers are a class of chemical substances used to inhibit the photo-oxidative degradation of polymers caused by ultraviolet radiation. They are widely used in a variety of materials, such as plastics, rubber, and coatings.

[0003] Benzotriazole UV stabilizers (BZT-UVs) are a class of emerging pollutants widely used in polymer materials, coatings, and paints. They exhibit high lipophilicity, environmental persistence, bioaccumulation, and potential toxicity. Some BZT-UVs (such as UV-320 and UV-328) have been banned or restricted in several countries and regions and are listed in the Stockholm Convention's list of persistent organic pollutants (POPs) and the European Union's list of substances of very high concern (SVHCs).

[0004] Benzotriazole UV stabilizer compounds are hydrophobic and weakly polar, and enter the natural environment in large quantities through natural weathering, wastewater from sewage treatment plants, and unregulated waste disposal. They have been widely detected in the environment and biological matrix.

[0005] Current monitoring methods for benzotriazole UV stabilizers primarily rely on targeted analysis, requiring the use of commercially available standards and failing to cover unknown analogues and environmental transformation products. Non-targeted screening based on high-resolution mass spectrometry holds immense potential in environmental science for comprehensively identifying a wide variety of unknown organic pollutants in complex environments. Traditional non-targeted screening methods require multiple rounds of data acquisition, are cumbersome and inefficient, and depend on manual spectral interpretation, resulting in limited coverage. Therefore, there is an urgent need to develop an efficient, comprehensive, and integrated analytical method capable of identifying unknown benzotriazole UV stabilizer pollutants and their transformation products.

[0006] Chinese patent document CN115389690A discloses a comprehensive identification method for benzotriazole ultraviolet absorber pollutants in the environment. This method includes the following steps: acquiring a database of suspected target compounds for benzotriazole ultraviolet absorber pollutants; performing liquid chromatography-mass spectrometry (LC-MS) analysis on the environmental sample to obtain data-dependent and data-independent acquisition data; performing matching analysis on the data-dependent acquisition data based on information about suspected target compounds to determine the structure of compounds matching the suspected target compounds; extracting characteristic fragment ions of benzotriazole ultraviolet absorber pollutants from the data-independent acquisition data to extract candidate compounds based on these characteristic fragment ions; and analyzing the chromatographic and mass spectrometric information related to candidate compounds in the data-dependent acquisition data to determine the structure of the candidate compounds. However, this method requires two LC-MS acquisitions of the environmental sample, which is time-consuming and affects the accuracy of compound identification. Furthermore, it requires manual screening of characteristic fragments, resulting in a significant workload.

[0007] Therefore, existing technologies cannot achieve simultaneous identification of targets, suspected targets, and non-targets through a single liquid chromatography-mass spectrometry acquisition. Summary of the Invention

[0008] This invention provides a method for identifying benzotriazole ultraviolet stabilizer contaminants. By combining single-data-dependent acquisition with molecular network analysis and computer-aided structural analysis, the method enables the simultaneous identification and characterization of target compounds, suspected compounds, and completely unknown compounds.

[0009] The technical solution of the present invention is as follows: A method for identifying contaminants in benzotriazole ultraviolet stabilizers, comprising the following steps: (1) Construct a database of potential targets for benzotriazole UV stabilizer pollutants; (2) Perform liquid chromatography-mass spectrometry analysis on the environmental sample to be tested, and obtain data-dependent acquisition data of the environmental sample to be tested in data-dependent acquisition mode; (3) Based on the information of compounds in the suspected target database, perform similarity analysis on the data-dependent collection data to determine the structure of suspected compounds that are similar to compounds in the suspected target database; (4) Relying on molecular networks, candidate compounds with mass spectrometry information similar to known benzotriazole pollutants are screened out; the chromatographic and mass spectrometry information related to the candidate compounds in the data-dependent acquisition data is analyzed to determine the structure of the candidate compounds.

[0010] Preferably, step (1) includes: (1-1) Explore benzotriazole UV stabilizer compounds detected in environmental samples reported in existing literature; (1-2) Screening for compounds with the 2-hydroxyphenylbenzotriazole structure in publicly available chemical databases; (1-3) Based on the phase I, phase II and phase III metabolic processes in organisms, predict the transformation products of the target compound in organisms; (1-4) The compounds from steps (1-1) and (1-2) and the conversion products from step (1-3) are combined to construct a database of potential targets.

[0011] In step (1-1), the existing literature includes literature from the following literature databases: Databases and websites including Web of Science, ScienceDirect, PNAS, Royal Society of Chemistry, SpringerLink, Wiley Online Library, and American Chemical Society Publications.

[0012] Preferably, step (1-2) includes: The similarity between compounds in publicly available chemical databases and the SMILES formula of 2-hydroxyphenylbenzotriazole was calculated based on the Tanimoto coefficient algorithm. If the similarity meets the preset conditions, the corresponding compound is identified as a compound having a 2-hydroxyphenylbenzotriazole structure.

[0013] In steps (1-2), the publicly available chemical databases include, but are not limited to, the Canadian Domestic Substances List (DSL), the US Toxic Substances Control Act List (TSCA), the US Chemical Data Report (CDR), the European Union Chemical Registration, Evaluation, Authorization and Restriction List (REACH), the Nordic Countries Chemical Substances List (SPIN), the Existing Chemical Substances List Produced or Imported in China (IECSC), the Japanese Industrial Safety and Health Law New Chemical Substances List (ISHA), the Korean Existing Chemical Substances List (KECI), and the Australian Industrial Chemicals List (AICIS).

[0014] In steps (1-3), the Compound Discoverer software is used to predict the phase I, phase II and phase III metabolic processes in the organism.

[0015] The aforementioned suspected target database contains compound information and mass spectrometry information of the compounds; the compound information includes the name and molecular formula of the compound, and the mass spectrometry information includes the precise mass number of the compound's adduct ions.

[0016] In step (2), the data-dependent acquisition mode is to use a first-stage mass spectrometry scan and a second-stage mass spectrometry scan under atmospheric pressure chemical ionization source positive ion conditions.

[0017] The data-dependent acquisition data includes primary mass spectrometry data and secondary mass spectrometry data of the sample.

[0018] Step (3) is a suspected target screening process. By analyzing whether there are precursor compounds in the environmental sample to be tested that match the suspected target compounds, the determination or possible structure of the precursor compounds can be obtained.

[0019] Preferably, step (3) includes: (3-1) Match the adduct ion mass number in the data-dependent acquisition data with the precise adduct ion mass number of the compounds in the suspected target database, and screen similar suspected precursor compounds from the compounds in the suspected target database; (3-2) Match the secondary fragment ions in the data-dependent acquisition data with the characteristic fragment ion information of compounds in the suspected target database, and screen out the matching precursor compounds from the suspected precursor compounds; (3-3) The structure of the precursor compound is determined based on the chromatographic retention time and secondary fragment ions of the precursor compound; the precursor compound is the suspected compound.

[0020] Step (4) is non-target screening. The characteristic fragment ions of benzotriazole UV stabilizer compounds are usually secondary fragment ions common to all benzotriazole UV stabilizer compounds. Therefore, based on the characteristic fragment ions, it is theoretically possible to infer and identify all benzotriazole UV stabilizer compounds in the environmental sample to be tested. At the same time, in this step, only candidate compounds that are different from the precursor compounds in step (4) are extracted and analyzed. By combining suspected target and non-target screening, the analysis process is simplified while achieving comprehensive identification of benzotriazole UV stabilizer compounds.

[0021] In step (4), the molecular network compares the mass spectrometric similarity between each MS2 spectrum in the data-dependent mass spectrometry data using a computer algorithm. Molecules with similar chemical and structural characteristics produce similar fragmentation patterns, and therefore their MS2 spectra have mass spectrometric similarity.

[0022] Preferably, step (4) includes: (4-1) Extract all ion features from the data-dependent mass spectrometry data, from MS 1 and MS 2 The data were used to plot the correlation between molecules with the same or related spectra, and a molecular network was constructed. (4-2) Unknown nodes that cluster with known benzotriazole UV stabilizer compounds are extracted from the molecular network as candidate compounds; (4-3) Analyze the chromatographic and mass spectrometric information related to the candidate compounds in the data-dependent acquisition data to determine the structure of the candidate compounds.

[0023] Step (4-3) includes obtaining the chromatographic retention time and secondary fragment ions of the candidate compound from the data-dependent acquisition data to determine the possible structure of the candidate compound.

[0024] Preferably, the method for identifying benzotriazole UV stabilizer pollutants of the present invention further includes target screening of the environmental sample to be tested: matching analysis of data-dependent acquisition data based on the chromatographic retention time and mass spectrometry information of the real standard to determine the target compound and concentration that matches the real standard.

[0025] Based on the above scheme, the present invention can achieve comprehensive identification of benzotriazole UV stabilizer pollutants in environmental samples based on targets, suspected targets, and molecular networks.

[0026] The method of this invention can be applied to a variety of complex environmental media. The environmental samples to be tested include water samples, solid samples, and biological samples containing benzotriazole pollutants. Among them, water samples can be industrial wastewater, sewage treatment plant influent and effluent, river water, surface water, groundwater, seawater, drinking water, etc. Solid samples can be sewage treatment plant sediment, water body sediment, sediment, soil, indoor dust, atmospheric particulate matter, etc. Biological samples can be human breast milk, urine, serum, animal organs, fish, birds, sharks, mollusks, plants, etc.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention constructs a database of suspected benzotriazole UV stabilizers based on text mining and the similarity coefficient of the 2-hydroxyphenylbenzotriazole structure. This database contains more benzotriazole compounds and has a wider coverage. It only requires a single data-dependent mass spectrometry acquisition process, saving sample acquisition time and improving the accuracy of subsequent compound identification. It also reduces the tedious and time-consuming manual matching and verification process, providing an effective solution for the comprehensive identification of benzotriazole UV stabilizer contaminants. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating the process of comprehensively screening benzotriazole UV stabilizer contaminants in the environment according to the present invention.

[0029] Figure 2 This is a detailed flowchart illustrating the comprehensive screening of benzotriazole UV stabilizer contaminants in the environment according to the present invention. Detailed Implementation

[0030] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be noted that the embodiments described below are intended to facilitate the understanding of the present invention and do not limit it in any way.

[0031] In implementing the identification method of this invention, the technical challenge lies in screening potential benzotriazole UV stabilizers from literature and publicly available chemical databases to construct a potential target database and subsequently identify candidate compounds. The potential target screening method based on the structural characteristics of benzotriazole UV stabilizers and the molecular network non-target screening are complementary identification methods. Combined with target identification methods, they enable comprehensive screening of benzotriazole UV stabilizers in samples from complex environments. The potential target database comprises known benzotriazole UV stabilizer compounds that may exist in the environment, compound information of the potential target compounds, and mass spectrometry information.

[0032] Specifically, according to some embodiments of the present invention, a method for comprehensively screening benzotriazole contaminants in the environment is provided, including the following steps A to E (see...). Figure 1 ): Step A: Based on the constructed database of suspected benzotriazole pollutants, which includes compound information and mass spectrometry information of the compounds.

[0033] According to an embodiment of the present invention, the suspected target database in this step is constructed through the following steps A1 to A4.

[0034] In step A1, text mining involves mining all compounds of benzotriazole UV stabilizers detected in environmental samples previously reported in articles.

[0035] In step A2, all compounds containing the 2-hydroxyphenylbenzotriazole structure (C1=CC=C(C(=C1)N2N=C3C=CC=CC3=N2)O) are screened from a public chemical database.

[0036] According to embodiments of the present invention, the publicly disclosed chemical databases include, but are not limited to, the Canadian Domestic Substances List (DSL), the US Toxic Substances Control Act List (TSCA), the US Chemical Data Report (CDR), the European Union Chemical Registration, Evaluation, Authorization and Restriction List (REACH), the Nordic Countries Chemical Substances List (SPIN), the Chinese Existing Chemical Substances List (IECSC), the Japanese Industrial Safety and Health Law New Chemical Substances List (ISHA), the Korean Existing Chemical Substances List (KECI), and the Australian Industrial Chemicals List (AICIS), etc.

[0037] According to an embodiment of the present invention, step A2 specifically includes: calculating the similarity between compounds in the publicly available chemical database and the SMILES formula of 2-hydroxyphenylbenzotriazole based on the Tanimoto coefficient algorithm, and screening out compounds that meet the preset similarity conditions.

[0038] Further screening involved calculating similarity using the Tanimoto coefficient algorithm and Python software. The SMILES formula for 2-hydroxyphenylbenzotriazole is C1=CC=C(C(=C1)N2N=C3C=CC=CC3=N2)O. In the field of environmental chemistry, SMILES formulas are a standard language for precisely describing the three-dimensional structure of molecules using strings, serving as a bridge between computer science and environmental chemistry.

[0039] As a preferred embodiment, if the similarity is not less than 0.6, the candidate compound corresponding to that similarity is identified as a compound having a 2-hydroxyphenylbenzotriazole structure. More preferably, manual inspection is performed to ensure accuracy based on the aforementioned similarity calculation and screening.

[0040] In step A3, based on the fact that metabolism in vivo includes phase I, phase II and phase III reactions, the transformation products of the target compound in vivo are screened and predicted.

[0041] According to embodiments of the present invention, the previously reported in vivo metabolic pathways and the well-defined molecular structures of benzotriazole compounds jointly determine the metabolic transformation pathways of benzotriazole compounds, including oxidation, reduction, methylation, demethylation, acetylation, and various conjugation reactions.

[0042] For example, the Compound Discoverer (version 3.1) software from Thermo Fisher can predict phase I and phase II metabolites of pollutants.

[0043] In step A4, a database of potential targets is constructed, including compounds identified through text mining and similarity screening, as well as products of metabolic transformation.

[0044] It is understandable that the compounds and metabolic transformation product compounds screened out by similarity are suspected target compounds, and the suspected target database includes compound information and mass spectrometry information of suspected target compounds.

[0045] According to embodiments of the present invention, the compound information includes the compound CAS number, name, and molecular formula, and the mass spectrometry information includes the precise mass number of the adduct ion. Optionally, the compound name can be the full name or abbreviation, etc.; the molecular formula is, for example, C1. 22 H 29 ON3, etc.; the precise mass number of the adduct ion can be, for example, the precise mass number of potassium addition, the precise mass number of proton addition, etc., with the precise mass number of proton addition being more common.

[0046] Step B: Perform liquid chromatography-tandem mass spectrometry analysis on the environmental samples. During the mass spectrometry analysis, fragment ion acquisition is performed in data-dependent acquisition (DDA) mode to obtain data-dependent acquisition data of the environmental samples to be tested.

[0047] According to an embodiment of the present invention, in step B, ultra-high performance liquid chromatography (UHPLC) tandem with high-resolution mass spectrometry is used to analyze environmental samples, which is beneficial for the analysis and detection of complex environmental samples.

[0048] According to an embodiment of the present invention, the liquid chromatography conditions are set to a gradient elution program, which can better separate possible benzotriazole UV stabilizer contaminants from environmental samples.

[0049] According to an embodiment of the present invention, the data-dependent acquisition mode of mass spectrometry acquisition is a first-stage mass spectrometry scan and a second-stage mass spectrometry scan under the positive ion conditions of an atmospheric pressure chemical ionization (APCI) ionization source.

[0050] Furthermore, data-dependent acquisition data includes first-order mass spectrometry (MS). 1 ) and secondary mass spectra (MS) 2 MS 1 Obtained via an electrostatic field orbital trap, with a scan range of mass-to-charge ratio m / z = 100-1000, MS 1 MS is used to obtain information such as the mass number of adduct ions. 2 Acquired via high-energy collisional dissociation (HCD) mode, the scan range depends on the MS. 1 The parent ion m / z is used to obtain secondary fragment ion information.

[0051] According to an embodiment of the present invention, data-dependent acquisition data requires high-resolution mass spectrometry data deconvolution analysis, and the signal intensity or threshold may be, for example, 10. 3 10 4 wait.

[0052] Furthermore, the method of the present invention also includes target screening of the environmental sample to be tested, specifically including step C, which involves matching analysis of data-dependent acquisition data based on the chromatographic retention time and mass spectrometry information of the real standard to determine the target compound and its concentration that matches the real standard. Target screening enables quantitative analysis of the target compound in the environmental sample to be tested.

[0053] According to embodiments of the present invention, obtaining real standards can be used to accurately determine characteristic fragment ions of benzotriazole pollutants, thereby enabling more accurate non-target screening. In addition, it can also be used to perform target screening of compounds in the environmental sample to be tested that match the real standards.

[0054] Step D: Based on the compound information and mass spectrometry information of the suspected target compound, perform matching analysis on the data-dependent acquisition data to determine the identifiable or possible structure of the compound in the environmental sample that matches the suspected target compound.

[0055] According to an embodiment of the present invention, step D is a suspected target screening, which involves analyzing whether there is a precursor compound in the environmental sample to be tested that matches the suspected target compound, thereby determining the precursor compound or its possible structure. Specifically, it includes sub-steps D1 to D3.

[0056] In sub-step D1, the adduct ion mass number in the data-dependent acquisition data is matched with the precise adduct ion mass number of the suspected target screening compound in the suspected target database, and similar suspected precursor compounds are screened from the suspected target compounds. In sub-step D2, secondary fragment ions from data-dependent acquisition data are compared with characteristic fragment ions ([C6H6N3)) of benzotriazole UV stabilizer compounds. + (m / z=120.0562), [C 12 H 10 N3O] + (m / z=212.0824), [C 13 H 10 N3O] + (m / z=224.0824) and [C 15 H 14 N3O] + (m / z=252.1137)) information was matched to screen for matching precursor compounds from the suspected precursor compounds; In sub-step D3, the identifiable or probable structure of the precursor compound is determined based on the chromatographic retention time and secondary fragment ions of the precursor compound, which is a compound that matches the suspected target compound.

[0057] By sequentially matching the adduct ion mass number and secondary fragment ions through the above sub-steps D1 to D3, it is beneficial to more accurately detect whether the sample contains suspected target compounds from the suspected target database. Furthermore, by analyzing the chromatographic retention time of the successfully matched compound and the mass spectrometry fragmentation pattern determined by the secondary fragment ions, the identifiable or possible structure of the precursor compound can be proposed.

[0058] Step E: Nodes with similar mass spectrometric characteristics to known benzotriazole UV stabilizer compounds form a molecular network. Molecular network analysis (MN) based on the Global Natural Product Social Molecular Network (GNPS) uses cosine similarity after spectral deblurring to construct correlation maps between spectrally related molecules, enabling rapid identification of potential contaminants. Candidate compounds are distinguished from compounds that match suspected target compounds.

[0059] According to an embodiment of the present invention, step E is a non-target screening. The characteristic fragment ions of benzotriazole pollutants are usually secondary fragment ions common to all benzotriazole pollutants. Therefore, based on the characteristic fragment ions, it is theoretically possible to infer and determine all benzotriazole pollutants in the environmental sample to be tested. At the same time, in this step, only candidate compounds that are different from the precursor compounds in step D are extracted and subsequently analyzed. By combining suspected target and non-target screening, the analysis process is simplified while achieving comprehensive identification of benzotriazole pollutants.

[0060] According to an embodiment of the present invention, step E specifically includes sub-steps E1 to E3: In sub-step E1, benzotriazole UV stabilizers are known to act as the parent ion MS. 1 Extract candidate molecular weights associated with molecular networks; In substep E2, from the MS corresponding to the EIC retention time... 1 Extract candidate molecular weights and candidate molecular formulas corresponding to the characteristic fragment ions; In sub-step E3, the candidate molecular formulas associated with the parent compound are determined as the molecular formulas of the candidate compounds.

[0061] Through the sub-steps E1 to E3 described above, the molecular formulas of possible candidate compounds are found based on the extracted characteristic fragment ions, such as C1. 24 H 23 ON3, and then proceed to step D to infer its possible structure based on mass spectrometry data.

[0062] According to embodiments of the present invention, the characteristic fragment ions of benzotriazole pollutants may include widely known and detected secondary fragment ions of benzotriazoles, such as [C6H6N3]. + (m / z=120.0562), [C 12 H 10 N3O] + (m / z=212.0824), [C 13 H 10 N3O] + (m / z=224.0824) and [C 15 H 14 N3O]+ (m / z=252.1137).

[0063] Step F involves analyzing the chromatographic and mass spectrometric information related to the candidate compounds in the data-dependent acquisition data to determine the possible structures of the candidate compounds.

[0064] According to an embodiment of the present invention, step F specifically includes obtaining the chromatographic retention time and secondary fragment ions of the candidate compound from data-dependent acquisition data to determine the possible structure of the candidate compound.

[0065] More specifically, based on the molecular formula of the candidate compound in step E, the chromatographic retention time and secondary fragment ions of the candidate compound are obtained from the data-dependent acquisition data. Reasonable candidate compounds are identified by analyzing the chromatographic retention time and the mass spectrometry fragmentation pattern based on the secondary fragment ions, and their possible structures are inferred.

[0066] According to embodiments of the present invention, the method of the present invention can be applied to a variety of complex environmental media. The environmental samples to be tested include water samples, solid samples, and biological samples containing benzotriazole pollutants. Among them, water samples can be industrial wastewater, sewage treatment plant influent and effluent, river water, surface water, groundwater, seawater, drinking water, etc.; solid samples can be sewage treatment plant sediment, water body sediment, sediment, soil, indoor dust, atmospheric particulate matter, etc.; biological samples can be human breast milk, urine, serum, animal organs, fish, birds, sharks, mollusks, plants, etc.

[0067] The following detailed description provides several specific embodiments to illustrate the technical solution of the present invention. It should be noted that the specific embodiments described below are merely examples and are not intended to limit the scope of the invention.

[0068] In the following examples, some reagents and detection instruments are described below: Reagents: List the 11 benzotriazole real standards in Table 1 below.

[0069] Liquid Chromatography-Mass Spectrometry (LC-MS): Ultra-High Performance Liquid Chromatography (UHPLC) and High Resolution Mass Spectrometry (HMS) System (ThermoScientific Vanquish) TM Flex System ultra-high performance liquid chromatography in tandem with Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific, USA); Column: Waters ACQUITY C18 (1.7 μm, 2.1 mm id × 100 mm).

[0070] Example 1 This embodiment is a laboratory testing embodiment, focusing on realizing the identification of benzotriazole contaminants present in spiked samples using an established method system. The specific steps include (see...). Figure 2 ): Step 1: Using text mining, we summarized the 54 benzotriazole compounds found in environmental samples as shown in Table 1, and selected 11 BZT-UVs with high detection rates and concentrations to purchase real standards.

[0071] Table 1

[0072] Step Two: Based on publicly available chemical databases including DSL, TSCA, CDR, REACH, SPIN, IECSC, ISHA, KECI, and AICIS, which contain information according to embodiments of the present invention, the structural similarity between compounds in the publicly available chemical databases and 2-hydroxyphenylbenzotriazole is calculated using the Tanimoto coefficient algorithm and Python. A score threshold of 0.6 is set, meaning that compounds with a similarity score greater than or equal to 0.6 are identified as having a 2-hydroxyphenylbenzotriazole structure. Since the real standard falls within the range of compounds screened in this step, this step further screens 46 benzotriazole homologues for which real standards were not purchased.

[0073] Step 3: Based on the 41 known biochemical pathways for pollutant metabolism in organisms shown in Table 2, the phase I and phase II metabolic transformation products of benzotriazole pollutants in organisms were predicted using ThermoFisher's Compound Discoverer (version 3.1) software.

[0074] Table 2

[0075] Step 4: Construct the benzotriazole homologues obtained in Steps 1 to 3 into a potential target data (i.e., a local database), including compound name, molecular formula, precise mass number of adduct ions, and secondary fragment ion information predicted by MegFrag software.

[0076] Step 5: Prepare a 1 mL methanol solution containing 11 real standards, each with a concentration of 100 μg / L, and then analyze it using a liquid chromatography-mass spectrometry instrument.

[0077] Liquid chromatography conditions: Column temperature was 35℃; the mobile phase consisted of a methanol solution (A) containing 0.5 mM ammonium acetate and an ultrapure aqueous solution (B) containing 0.5 mM ammonium acetate. The gradient elution program was as follows: first, 70% A was held for 1 min; then A was increased to 100% over 14 min; next, 100% A was held for 5 min; then A was decreased to 70% over 0.1 min; finally, 70% A was held for 4.9 min; the mobile phase flow rate was 0.3 mL / min; and the injection volume was 5 μL.

[0078] Mass spectrometry conditions: Ion source: atmospheric pressure chemical ionization source in positive ion mode; spray voltage: 3500 V; ion transfer tube temperature: 300℃; nebulization temperature: 400℃; sheath gas, purge gas, and auxiliary gas pressures: 35, 1, and 10 Arb, respectively. Data-dependent acquisition mode parameters: MS 1 Acquired via electrostatic orbital trap, resolution 120000 FWHM, scan range m / z = 100-1000, maximum injection time 100 ms, automatic gain control target 3e6, S-lens RF 60%. 2 Acquired via HCD mode, resolution 60000 FWHM, collision energy set at 10%, 30%, and 50%, MS. 1 The parent ion is isolated by an electrostatic orbital trap with an isolation window width of m / z=1. Fragment ions are detected by the electrostatic orbital trap, and the scanning range depends on the parent ion's m / z.

[0079] Step 6: Use the data from the data-dependent acquisition mode in Step 5 to screen for suspected targets in Compound Discoverer (version 3.1) software, identify benzotriazole compounds and predicted biotransformation products recorded in the list. The process is as follows: (1) Deconvolve the high-resolution mass spectrometry data, with a signal intensity threshold of 10e4; (2) Match the suspected target database, including two types of mass spectrometry data matching: addition ion mass number matching in primary mass spectrometry and fragment ion matching in secondary mass spectrometry. In primary mass spectrometry matching, the mass spectrometry deviation is 10ppm, the isotope threshold is 75%, and the signal-to-noise ratio is 5:3. Analyze the chromatographic retention time and mass spectrometry fragmentation pattern of the precursor compounds that were successfully matched with the aforementioned features, and propose the confirmed or possible structures.

[0080] Step 7: Extract all ion features from the data-dependent acquisition mode data in Step 5 using GNPS and MS-DIAL (version 4.9), and based on the vector similarity after spectral deblurring, extract the ion features from MS-DIAL. 1 and MS 2The data was used to plot the correlation maps of molecules with the same or related spectra. Data preprocessing stage: The original files were converted to a centralized .abf format using Analysis Base File Converter, and the characteristic quantification table (.txt) and MS-DIAL were exported. 2 The spectral summary (.mgf) was uploaded to the GNPS network platform for feature-based molecular network analysis (FBMN) workflow processing. The algorithm adopted a precursor / fragment mass tolerance of 0.002 Da and a cosine threshold of 0.6. The generated molecular network was visualized using Cytoscape v3.10.2. Unknown nodes clustered with the parent BZT-UVs were prioritized as candidate compounds. Benzotriazole compounds not recorded in the chemical industry list and not belonging to the predicted biotransformation products, industrial intermediates or impurities were identified. The process is as follows: (1) Extract 4 characteristic fragment ions, namely [C6H6N3] + (m / z=120.0562), [C 12 H 10 N3O] + (m / z=212.0824), [C 13 H 10 N3O] + (m / z=224.0824) and [C 15 H 14 N3O] + (2) Based on the retention time of the EIC plot, from the corresponding MS 1 Extract the molecular formula of the candidate compound corresponding to the characteristic fragment ion, the difference of which is the precursor compound successfully matched in step six; (3) Analyze the chromatographic retention time and mass spectrometry fragmentation pattern of the candidate compound under the data-dependent acquisition mode based on the molecular formula, match reasonable candidates based on mass spectrometry data, and propose a definite or possible structure.

[0081] It is understandable that, furthermore, the benzotriazole pollutants identified and characterized in steps six and seven can be semi-quantitatively analyzed using structurally similar standards; and target screening can be performed on the environmental samples to be tested based on real standards. In this embodiment, since the samples to be tested are real standards, the target screening process will not be described in detail.

[0082] Through the specific steps described above, all 11 benzotriazole compounds in the standard solution were identified with a 100% accuracy rate, demonstrating the reliability of the identification method and its ability to accurately identify benzotriazole contaminants present in samples. Specifically, both step six (suspected target screening) and step seven (non-target screening) achieved accurate identification of benzotriazole contaminants in the samples. These two methods complement each other, ensuring comprehensive identification of benzotriazole contaminants in the environment.

[0083] Example 2 Similar to the factual process in Example 1, the spiked methanol solution was replaced with spiked real environmental sediment samples. The purpose of this example is to test the ability of this method to identify benzotriazole pollutants in environmental samples under matrix interference conditions.

[0084] The operating steps are basically the same as in Example 1. The difference is that in step five, the actual environmental samples undergo pretreatment, including accelerated solvent extraction, gel permeation chromatography purification, silica gel column purification, and rotary evaporation followed by nitrogen blowing for reconstitution. The results show that all 11 spiked benzotriazole contaminants were identified, indicating that this method is suitable for cutoff in complex environments and is less affected by matrix interference.

[0085] Example 3 The purpose of this embodiment is to test the method's comprehensive ability to identify benzotriazole pollutants in environmental samples. The collected environmental samples were freshwater biological samples (snails, shrimp, and freshwater fish).

[0086] The operating steps are basically the same as in Example 1. The difference is that in step five, the biological sample undergoes pretreatment, including accelerated solvent extraction, gel permeation chromatography purification, silica gel column purification, and rotary evaporation followed by nitrogen blowing for reconstitution. The results showed that a total of 23 benzotriazole pollutants were identified, including 11 target compounds (Allyl-bzt, UV-P, UV-PS, UV-234, UV-326, UV-327, UV-328, UV-329, UV-350, UV-360, and UV-928), 3 biotransformation products (structures shown in Formulas I to III) (as shown in Table 3), and 10 impurity benzotriazole compounds (structures shown in Formulas 1 to 10) (as shown in Table 4). Both benzotriazole biotransformation products and impurity benzotriazole compounds were discovered for the first time in environmental media using this identification method, indicating that this method can comprehensively identify benzotriazole pollutants in the environment and fills the existing technological gap in the field of environmental analytical chemistry for benzotriazole pollutants.

[0087] Table 3

[0088] In Table 3, compounds of formulas I to III are the identified or possible structures of the biotransformation products of BZT-UVs.

[0089] Table 4

[0090] In Table 4, compounds of formulas 1 to 10 are the identified or possible structures of the impurity class BZT-UVs.

[0091] Example 4 The purpose of this embodiment is to test the high-throughput identification capability of this method for benzotriazole pollutants in a large-scale environmental sample collection. The environmental samples collected were 87 sediment and biological samples from Qiandao Lake in Zhejiang Province, China.

[0092] The operational steps are basically the same as in Example 1. The difference is that in step five, the biological samples undergo pretreatment, including accelerated solvent extraction, gel permeation chromatography purification, silica gel column purification, and rotary evaporation followed by nitrogen blowing for reconstitution. The entire identification system completes the analysis of all environmental samples within 24 hours, and the identified benzotriazole contaminants with authentic standards have been validated by the standards, demonstrating that this method can accurately, rapidly, and with high throughput comprehensively identify benzotriazole contaminants in the environment.

[0093] The results of the above embodiments collectively demonstrate that the comprehensive identification method for benzotriazole pollutants in the environment involved in this invention has high accuracy, complements the screening methods for suspected targets and non-targets, can be applied to various complex environmental media, is minimally affected by matrix interference, identifies a wide range of compounds, and can efficiently identify known, unknown, and transformation products, and has rapid and high-throughput characteristics, enabling the identification of large-scale environmental samples in a short time. Therefore, the method of this invention has universal applicability and broad application prospects.

[0094] The embodiments described above provide a detailed explanation of the technical solutions and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, additions, and equivalent substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for identifying a benzotriazole ultraviolet stabilizer contaminant, characterized by, The method comprises the following steps: (1) constructing a suspected target database of benzotriazole ultraviolet stabilizer pollutants; (2) analyzing the environment sample to be tested by liquid chromatography-mass spectrometry, and obtaining data-dependent acquisition data of the environment sample to be tested in a data-dependent acquisition mode; (3) performing similarity analysis on the data-dependent acquisition data based on the information of the compounds in the suspected target database, and determining the structure of the suspected compound similar to the compounds in the suspected target database; (4) screening candidate compounds similar to the mass spectrometry information of known benzotriazole pollutants from a molecular network; analyzing the chromatographic information and mass spectrometry information related to the candidate compounds in the data-dependent acquisition data to determine the structure of the candidate compounds.

2. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 1, characterized by, Step (1) comprises: (1-1) mining benzotriazole ultraviolet stabilizer compounds detected in environment samples reported in existing literatures; (1-2) screening compounds with 2-hydroxyphenyl benzotriazole structure in a public chemical database; (1-3) predicting the conversion products of the target compounds in vivo based on phase I, phase II and phase III metabolic processes in vivo; (1-4) combining the compounds of steps (1-1) and (1-2) and the conversion products of step (1-3) to construct a suspected target database.

3. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 2, characterized by, Step (1-2) comprises: calculating the similarity between the compounds in the public chemical database and the SMILES formula of the 2-hydroxyphenyl benzotriazole structure based on the Tanimoto coefficient algorithm; in the case where the similarity meets the preset condition, the corresponding compound is determined as a compound with 2-hydroxyphenyl benzotriazole structure.

4. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 2, characterized by, In step (1-3), the phase I, phase II and phase III metabolic processes in vivo are predicted by Compound Discoverer software.

5. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 1 or 2, characterized by, The suspected target database contains compound information and mass spectrometry information of the compounds; the compound information includes the name and molecular formula of the compound, and the mass spectrometry information includes the accurate mass number of the adduct ion of the compound.

6. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 1, characterized by, The data-dependent acquisition data includes primary mass spectrometry data and secondary mass spectrometry data of the sample.

7. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 1, characterized by, Step (3) comprises: (3-1) matching the adduct ion mass number in the data-dependent acquisition data with the accurate mass number of the adduct ion of the compounds in the suspected target database, and screening similar suspected precursor compounds from the compounds in the suspected target database; (3-2) matching the secondary fragment ions in the data-dependent acquisition data with the characteristic fragment ion information of the compounds in the suspected target database, and screening the matched precursor compounds from the suspected precursor compounds; (3-3) determining the structure of the precursor compound based on the chromatographic retention time and the secondary fragment ions of the precursor compound; the precursor compound is the suspected compound.

8. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 1, characterized by, Step (4) comprises: (4-1) Extract all ion features in the data-dependent mass spectrometry data, from MS 1 and MS 2 data to draw the correlation graph of the same and related molecules, and construct a molecular network; (4-2) extracting unknown nodes clustered with known benzotriazole ultraviolet stabilizer compounds from the molecular network as candidate compounds; (4-3) analyzing the chromatographic information and mass spectrometry information related to the candidate compounds in the data-dependent acquisition data to determine the structure of the candidate compounds.

9. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 8, characterized by, Step (4-3) comprises: obtaining the chromatographic retention time and secondary fragment ions of the candidate compound from the data-dependent acquisition data to determine the possible structure of the candidate compound.

10. The method for identifying a benzotriazole ultraviolet stabilizer contaminant according to claim 1, characterized by, It also comprises target screening on the sample to be tested: based on the chromatographic retention time and mass spectrum information of the real standard, the data-dependent acquisition data is analyzed by matching to determine the target compound and concentration matched with the real standard.

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