A method for identifying and prioritizing toxic effect compounds in complex environmental samples

Abstract

The present invention provides a method for identifying and prioritizing toxic effect compounds in complex environmental samples, and belongs to the field of environmental analytical chemistry. GC×GC-TOF MS with high separation ability, peak capacity and sensitivity is used to achieve simultaneous effective separation of thousands of organic pollutants in environmental samples, providing guarantee for accurate identification of unknown compounds; a large-scale toxic substance database (ToxCast) covering multiple substances and multiple targets is used to quickly screen out pollutants in environmental samples that will have adverse effects on human health; toxic equivalents are calculated based on the toxic effects of each pollutant and its concentration in the environment, the main risk driving factors are determined, and false positive results are excluded in combination with the absorption, distribution, metabolism and excretion characteristics of pollutants in the human body, so as to achieve reasonable inference from in vitro to in vivo analysis; a bipartite network is constructed by a systems biology method to reveal the complex phenotypic levels that need to be given priority attention to the adverse effects of pollutants on human health, which can not only explain the internal causes of previous epidemiological survey results at the molecular level, but also help to discover new pathogenic pathways.

Description

Technical Field

[0001] The invention relates to a method for identifying and prioritizing toxic effect compounds in complex environmental samples, and belongs to the field of environmental analytical chemistry. Background Art

[0002] The adverse effects of environmental pollution on human health are closely related to the organic components in it. Although the health effects of some known pollutants in the environment have been studied, these only account for a small part of the total organic carbon in the complex environmental components, and other key compounds and molecular mechanisms that lead to adverse human outcomes may be overlooked. Due to the extremely complex organic components in the environment, it is challenging to fully understand and identify pollutants in environmental samples that pose a high risk to human health.

[0003] Compared with traditional one-dimensional chromatography, comprehensive two-dimensional gas chromatography greatly increases chromatographic resolution, peak capacity and sensitivity, and is a powerful tool for analyzing organic pollutants in complex environmental samples. In order to quickly evaluate the toxicity of a large number of chemicals, the U.S. Environmental Protection Agency has launched a large-scale toxicity prediction (ToxCast) project since 2007. Through in vitro assays and computer modeling, it has currently evaluated the activity of about 4,500 chemicals covering more than 700 endpoints and 300 signaling pathways. Exposome research combined with the concept of adverse outcome pathways will help to break the understanding of existing organic components in the environment, identify major risk drivers from complex mixtures and understand the adverse reaction mechanisms induced by them, and reveal the key link between environmental exposure and adverse health outcomes in humans. Summary of the invention

[0004] The purpose of the present invention is to provide a method for identifying and prioritizing toxic effect compounds in complex environmental samples, combining comprehensive two-dimensional gas chromatography with the ToxCast database to screen toxic effect pollutants in the environment, and prioritizing them by evaluating the relative contribution of each component, and revealing the analytical method of the main chemical-biological effect pathways through systems biology.

[0005] The method provided by the present invention for identifying and prioritizing toxic effect compounds in complex environmental samples comprises the following steps:

[0006] (1) Sample pretreatment

[0007] The complex environmental samples are extracted and concentrated by using the accelerated solvent extraction method to obtain a concentrated extract;

[0008] (2) Analyze the concentrated extract using GC×GC-TOFMS;

[0009] (3) Identify the molecular structure of unknown pollutants and screen toxic effect compounds using the ToxCast database;

[0010] (4) Prioritize pollutants based on their toxicity factors, exposure levels, and toxicokinetic properties in humans;

[0011] (5) When using bipartite network visualization, priority should be given to the biological effects of pollutants to reveal the main action pathways.

[0012] In step (1) of the above method, the complex environmental sample is extracted using n-hexane: dichloromethane (1:1, v / v) as the extraction solvent;

[0013] The extract is concentrated by rotary evaporation and a steady nitrogen flow to obtain a concentrated extract;

[0014] After the concentration, the method may further include filtering the concentrated extract using a 0.22 μm organic filter membrane to collect the filtrate;

[0015] In step (2) of the above method, the specific conditions of GC×GC-TOFMS can be: chromatographic column combination is Rxi-5ms (30m×0.25mm×0.25μm)+Rxi-17Sil MS (1m×0.25mm×0.25μm); carrier gas flow rate is 1.0mL / min; non-split injection; injection port temperature is 280°C; the first column oven starts from 60°C (1min), and is heated to 100°C at a rate of 20°C / min, maintained for 1min, and then heated to 310°C at a rate of 2.5°C / min, and maintained for 5min; the second column oven is always 10°C higher than the first column oven; the modulator cycle is 8 seconds, which is 25°C higher than the second column oven; the transmission line temperature is 310°C; EI mode; ionization energy is 70eV; ion source temperature is 250°C; data acquisition range is m / z 20-1000; acquisition speed is 180 spectra / second;

[0016] The operation of step (3) of the above method is as follows: the massive data obtained by GC×GC-TOFMS analysis is matched with mass spectral information and retention index comparison through the NIST spectral library, and the identification results are divided into three categories according to the confidence level: characteristic fragments to illustrate substituents (level 3), spectral library search to propose possible structures (level 2) and reference standards to confirm structures (level 1); then with the help of the EPA ToxCast project database, the compounds that will have toxic effects on humans are screened out; the ClassyFire method is used to classify the structures according to the functional groups contained in different compounds, and the functional uses of the identified compounds are characterized through the Chemicals and Products Database (CPDat);

[0017] The operation of step (4) of the above method is: according to the required concentration (AC) at 50% maximum activity corresponding to the effective positive reference extracted from the ToxCast data set50 ) Calculate the toxicity equivalent factor (TEF) of each chemical in each activity test, and calculate its toxicity equivalent (TEQ) and toxicity contribution ratio (TEQ%) in combination with the exposure concentration of each chemical (quantitative or semi-quantitative results); Use ADMETlab software to predict the toxicokinetic properties (absorption, distribution, metabolism and excretion) of different compounds in the human body, so as to achieve effective inference from in vitro to in vivo analysis results and clarify the main risk drivers when the human body is exposed to multiple chemicals in a complex environment;

[0018] The operation of step (5) of the above method is: by calculating the "gene score", the research results of the pollutants of priority concern determined in step (4) in multiple cell lines at the same molecular target are summarized, and then a bipartite network is constructed using Gephi software to visualize the complex and intertwined chemical-biological effect relationship, thereby explaining the various pathways and processes of potential adverse results predicted from ToxCastDB at a multi-scale level, revealing the main human exposure endpoints and action pathways of highly toxic contributing pollutants in environmental samples,

[0019]

[0020] where

[0021]

[0022]

[0023] Where G(X, g) is the gene score of compound X in gene g, n assay (g) is the number of cell features corresponding to gene g, {A1,…,A nassay(g)} is the set of all cell features, Z(X, A) is the standardized score of chemical X and cytotoxic endpoint A, and for chemical X with two or more cytotoxic endpoints, the AC scores corresponding to these endpoints are summarized. 50 The logarithmic set of values ​​(log 10 ), m(X) represents the median of the set, and the median absolute deviation (MAD) of the set is calculated. global is the median MADs of all chemicals.

[0024] Compared with the existing toxic compound screening methods, the present invention has the following advantages:

[0025] (i) GC×GC-TOFMS with high separation ability, peak capacity and sensitivity is used to effectively separate thousands of organic pollutants in environmental samples, providing a guarantee for the subsequent structural identification of unknown compounds.

[0026] (ii) The ToxCast database covering multiple substances and multiple targets is used to quickly screen out pollutants that may have adverse biological effects on the human body.

[0027] (iii) Combine the ADME properties of pollutants to eliminate false positive results and achieve reasonable extrapolation from in vitro to in vivo analysis

[0028] (iv) By constructing a bipartite network using a systems biology approach, we reveal the complex phenotypic hierarchy of the adverse effects of environmental pollution on human health, which can not only clarify the underlying causes of previous epidemiological findings at the molecular level, but also help discover new pathogenic pathways. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is the total ion current chromatogram of organic compounds in complex atmospheric samples determined by GC×GC-TOFMS in the present invention.

[0030] Figure 2 These are the ToxCast compounds in the atmosphere identified in the present invention.

[0031] Figure 3 The pathways of action of ToxCast compounds in the atmosphere that require priority attention and that may cause adverse effects on human health. DETAILED DESCRIPTION

[0032] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0033] Unless otherwise specified, the materials and reagents used in the following examples can be obtained from commercial sources.

[0034] Air pollution poses a major threat to public health worldwide. Studies have found that short-term or long-term exposure to PM 2.5There is a strong association with cardiovascular, respiratory and all-cause mortality. This negative impact depends largely on the organic components in the atmosphere. Over the past few decades, PM mass concentrations have dropped significantly due to strategies aimed at reducing SO2, NOx and vehicle exhaust emissions. However, the successful reduction in PM mass concentration does not necessarily mean a reduction in the oxidative potential, one of the possible drivers of acute health effects in air pollution. This means that refined pollution prevention and control measures targeting key effect components in atmospheric particulate matter rather than just the total PM amount have become more important for public health. In addition, clinicians have been shown to have great potential to reduce risks by developing population-based intervention strategies and control disease progression through specific therapies based on pathophysiological pathways. Traditional targeted analysis only accounts for a small part of the total organic carbon in ambient air, and some key chemicals and important biological mechanisms may be overlooked. High-throughput non-targeted screening methods are expected to prospectively identify new pollutants that need to be given priority in the atmosphere, reveal the key causal relationship between air exposure and adverse health outcomes in humans, and help launch more effective and targeted air pollution prevention and control and clinical intervention treatment measures.

[0035] The following is an example of screening and prioritizing toxic effect compounds in complex environmental samples (taking atmospheric gas phase and fine particulate matter samples in Beijing as an example). It includes the following steps:

[0036] (1) Atmospheric gas phase and fine particulate matter samples were collected from November 2018 to January 2019 at the Beijing Urban Ecosystem Research Station using a high-flow active sampler. Simple sample pretreatment included accelerated solvent extraction using n-hexane: dichloromethane (1:1, v / v) as the solvent, concentration of the extract using rotary evaporation and steady nitrogen flow, filtration using a 0.22 μm organic filter membrane, and collection of the filtrate. GC×GC-TOFMS was used to effectively separate thousands of volatile and semi-volatile organic pollutants in the collected atmospheric samples ( Figure 1 ).

[0037] (2) The detected atmospheric compounds were identified through NIST spectral library search, retention index comparison, isotope pattern verification and ion element composition analysis. Among them, 865 compounds were classified as "tentative candidates", 217 compounds with a deviation of less than 2% from the reference retention index were classified as "possible structures", and 30 compounds confirmed using commercial standards were designated as "confirmed structures". Combined with the ToxCast database, 76 compounds in the atmosphere that have toxic effects on humans were screened out ( Figure 2), which can be divided into eight categories according to the main functional groups, including alkanes (n=2), carboxylic acids / esters (n=8), dicarboxylates (n=4), ketolactones (n=3), phenols (n=9), phthalates (n=5), polycyclic aromatic hydrocarbons (n=9) and others (n=36). Among them, 21 compounds have been less concerned before, and 5 are reported for the first time in the atmosphere, including isopropyl phenol, (E) anethole, ethylhexyl benzoate, 2,4-decadienal and N-methylphthalimide. An extended retrospective screening was carried out through quality defect analysis, and some analogs of these ToxCast chemicals were found, indicating the presence of an important subset of typical new pollutants in the atmosphere.

[0038] (3) The toxic equivalents of these compounds were calculated by combining the content of ToxCast compounds identified in the atmosphere (median concentration of pollutants in each sample) and the toxic dose-effect relationship (TEF). The results showed that the toxic contribution ratios of these compounds to 50 biological endpoints in blood vessels, lungs, liver, kidneys, prostates and bone tissues varied greatly. The toxic effect of the same compound at a certain target will be affected by its exposure form (gas phase or particle phase), exposure time and cell type. Combined with the ADME characteristics of pollutants, it was found that some chemicals that are more active in in vitro tests may not cause high toxicity in vivo due to limited absorption, distribution and related metabolism and excretion processes. Based on this, 29 high-risk pollutants in the atmosphere that need priority attention were further screened out, including polycyclic aromatic hydrocarbons, phenols, benzoates, thiophenes, and isocyanates (Table 1).

[0039] Table 1 Priority ranking of ToxCast compounds in the atmosphere

[0040]

[0041]

[0042] (4) 267 chemical-effect pathways involving 29 air pollutants and 31 human molecular targets were mapped in a bipartite network ( Figure 3). Nodes located in the center of the network represent that the molecular target is related to more pollutants, such as CISand TRANS in the liver (green domain). Nodes located at the edge represent greater specificity, such as Pselectin, IL6, MCP1, Eselectin and uPAR in blood vessels (red domain) and HLADR and IL1α in the lungs (purple domain). The larger the node label, the more molecular targets will be affected by the pollutant. The edge thickness of each compound-target is proportional to the corresponding gene score, which reveals the mechanism of action of key toxic components in the atmosphere leading to adverse health outcomes in the human body. For example, 4-nonylphenol, 2,4-di-tert-butylphenol, and toluene-2,4-diisocyanate, rather than the well-known inflammatory components PAHs, significantly affect the level of major histocompatibility complex class II α protein and trigger lung inflammatory response by regulating gene expression. 2,4-Dimethylphenol, 1-naphthol, 2,4-di-tert-butylphenol and 4-nonylphenol, pyrene and indenyldiol (1,2,3-cd)pyrene, and di(2-ethylhexyl)phthalate play an important role in increasing the expression of the cell adhesion molecule VCAM-1 in blood vessels. In addition to the signaling of inflammatory chemokines, vascular endothelial growth factor and plasminogen, other biological processes such as cell proliferation, cell morphology and cell death in the vascular system are also strongly disturbed by pollutants in the atmosphere. In addition to the cardiovascular and lungs that have been reported previously, atmospheric pollutants may cause adverse reactions in the liver, kidneys, prostate and bones by changing cell proliferation, protein stability, receptor binding and regulating transcription factor activity.

[0043] This invention provides a new way to explore the key causal relationship between exposure to organic components in complex environmental samples and adverse health outcomes in the human body (from full component detection in complex environmental samples to identification of toxic effect compounds, and then to priority sorting and identification of major biological pathways). It can prospectively identify key organic components in the environment that will have adverse effects on human health, including some new pollutants that contribute more to toxicity than known compounds. It can also identify important compound-biological effect pathways from large data sets, propose previously neglected human exposure endpoints, promote and expand the comprehensive assessment of pollutants with higher risks to human health in complex environmental samples and the understanding of their stress-induced adverse reactions in the human body, and provide a scientific basis for improving existing environmental risk management.

[0044] The specific examples described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying and prioritizing toxic effect compounds in complex environmental samples, comprising the following steps: (1) Sample pretreatment The complex environmental samples are extracted and concentrated by using the accelerated solvent extraction method to obtain a concentrated extract; (2) Analyze the concentrated extract using GC×GC-TOFMS; (3) Identify the molecular structure of unknown pollutants and screen toxic effect compounds using the ToxCast database; (4) Prioritize pollutants based on their toxicity factors, exposure levels, and toxicokinetic properties in humans; The operation of step (4) is as follows: according to the concentration required for 50% maximum activity (AC 50 ) Calculate the toxicity equivalent factor (TEF) of each chemical in each activity test, and calculate its toxicity equivalent (TEQ) and toxicity contribution ratio (TEQ%) based on the exposure concentration of each chemical (quantitative or semi-quantitative results); Use ADMETlab software to predict the toxicokinetics (absorption, distribution, metabolism and excretion) of different compounds in the human body, so as to achieve effective inference from in vitro to in vivo analysis results and clarify the main risk drivers when the human body is exposed to multiple chemicals in a complex environment; (5) When using bipartite network visualization, priority should be given to the biological effects of pollutants to reveal the main action pathways; The operation of step (5) is as follows: by calculating the "gene score", the research results of the pollutants of priority concern identified in step (4) in multiple cell lines at the same molecular target are summarized, and then a bipartite network is constructed using Gephi software to visualize the complex and intertwined chemical-biological effect relationship, thereby explaining the various pathways and processes of potential adverse results predicted from ToxCastDB at a multi-scale level, revealing the main human exposure endpoints and action pathways of highly toxic contributing pollutants in environmental samples. Where G(X, g) is the gene score of compound X in gene g, n assay (g) is the number of cell features corresponding to gene g, {A1,…,A nassay(g) } is the set of all cell features, Z(X, A) is the standardized score of chemical X and cytotoxic endpoint A, and for chemical X with two or more cytotoxic endpoints, the AC scores corresponding to these endpoints are summarized. 50 The logarithmic set of values ​​(log 10 ), m(X) represents the median of the set, and calculates the median absolute deviation (MAD) of the set, M global is the median MADs of all chemicals.

2. The method according to claim 1, characterized in that: Complex environmental samples were extracted using n-hexane: dichloromethane (1:1, v / v) as the extraction solvent; The extract was concentrated by rotary evaporation and steady nitrogen flow to obtain a concentrated extract.

3. The method according to claim 1 or 2, characterized in that: In step (2), the specific conditions of GC×GC-TOFMS are as follows: chromatographic column combination is Rxi-5ms (30 m×0.25 mm×0.25 μm) + Rxi-17Sil MS (1 m×0.25 mm×0.25 μm); carrier gas flow rate is 1.0 mL / min; splitless injection; injection port temperature is 280°C; the first column oven starts from 60°C (1 min), increases to 100°C at a rate of 20°C / min, maintains for 1 min, and then increases to 310°C at a rate of 2.5°C / min, maintains for 5 min; the second column oven is always 10°C higher than the first column oven; the modulator cycle is 8 seconds, which is 25°C higher than the second column oven; the transfer line temperature is 310°C; EI mode; ionization energy is 70 eV; ion source temperature is 250°C; data acquisition range is m / z 20-1000; acquisition speed is 180 spectra / second.

4. The method according to claim 1 or 2, characterized in that: The operation of step (3) is as follows: the massive data obtained by GC×GC-TOFMS analysis is matched with mass spectral information and retention index comparison through the NIST spectral library, and the identification results are divided into three categories according to the confidence level: characteristic fragments to illustrate substituents (level 3), spectral library search to propose possible structures (level 2) and reference standards to confirm structures (level 1); then with the help of the EPA ToxCast project database, the compounds that will have toxic effects on humans are screened out; the ClassyFire method is used to classify the structures according to the functional groups contained in different compounds, and the functional uses of the identified compounds are characterized through the Chemicals and Products Database (CPDat).

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