Abstract
Benzene is known to be a common toxic industrial chemical, and prolonged benzene exposure may cause nervous system damage. At present, there were few studies on benzene-induced neurological damage. This research aimed to identify the protein biomarkers to explore the mechanism of nervous system damage caused by benzene. We established a benzene poisoning model of C57 mice by gavage of benzene-peanut oil suspension and identified differentially expressed proteins (DEPs) in brain tissue using tandem mass tag (TMT) proteomics. The results showed a significant weight loss and decrease in leukocyte and neutrophil counts in benzene poisoning mice compared to the control group. We also observed local cerebral oedema and small vessel occlusion in the cerebral white matter of benzene poisoning mice. TMT proteomic results showed that a total 6,985 proteins were quantified, with a fold change (FC) > 1.2 (or < 1/1.2) and P value <0.05 were considered as DEPs. Compared with the control group, we identified 43 DEPs, comprising 14 upregulated and 29 downregulated proteins. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis results showed that the candidate proteins were mainly involved in cholesterol metabolism, complement and coagulation cascades, african trypanosomiasis, PPAR signaling pathway, and vitamin digestion and absorption. Three proteins, 2-hydroxyacylsphingosine 1-beta-galactosyltransferase (UGT8), Apolipoprotein A-I (APOA1) and Complement C3 (C3) were validated using immunoblotting and immunohistochemical. In conclusion, our study preliminarily investigated the mechanism of benzene toxicity to the nervous system by analyzing DEPs changes in the brain.
Keywords: benzene poisoning, nervous system, TMT proteomics, mice
Introduction
Benzene is a moderately toxic organic which is a colourless oily liquid and volatile at room temperature. It is miscible with alcohol, ether and acetone, and widely used in many fields such as paints, pharmaceuticals and shoe-making.1 In developing countries, benzene exposure remains an extremely hazardous occupational disease and epidemic.2 Benzene is mainly present within vapour in industrial production environments and can be absorbed through the respiratory tract, digestive tract and skin.3 Benzene is known to cause serious damage to the haematopoietic system. Persistent exposure to benzene leads to a range of haematological toxicities including leukopenia, thrombocytopenia, pancytopenia and even leukaemia.2,4,5 Therefore, benzene was classified as a carcinogenic to human by the International Agency for Research on Cancer (IARC).6 In addition to the haematopoietic system, benzene can also cause serious damage to the nervous system, such as nausea and vomiting, headache and dizziness, and blurred consciousness.7 However, few studies have been conducted on the neurological damage after benzene poisoning, and the mechanism of its toxicity is still unclear.
Currently, the diagnostic criteria for benzene poisoning were mainly based on cell counts and bone marrow imaging for diagnosis and grading.4 In most cases, the neurological damage was limited to the patient’s own subjective description of symptoms, and there was no objective information for reference. As early as 1958, Iannaccone A8 used histochemical methods to study the histological changes in the anterior lobe of the pituitary gland following benzene poisoning in rats. He found that the obvious change in nerve cells after benzene poisoning was the blistering of the cytoplasm, sometimes presented as “signet-ring”, which may be related to the increased secretion of protein hormones. Van et al.9 carried out a community-based case-control study of childhood brain cancer in the United States and Canada under industrial environmental conditions (benzene exposure), and they thought that benzene may affect the neurological system of children and called for the reduction of benzene levels in industrial environments. Hu et al.10 reported a case of chronic benzene poisoning in a 41-year-old woman with clinical manifestations of loss of appetite, easy fatigue and memory loss. Doctors used magnetic resonance imaging (MRI) to observe the brain structural changes in patient with chronic benzene poisoning. The results showed that large abnormal signals observed in the frontal and parietal white matter of both hemispheres which accompanied by localised cerebral oedema and shallow sulci.
The absence of standard guidelines and references for brain damage of benzene poisoning in clinical practice can easily lead to misdiagnosis or missed diagnosis, which may result in serious damage or disability if not treated in time. A high-throughput systems biology approach may provide an effective research direction for the study of benzene poisoning. In this study, we used tandem mass tag (TMT) proteomics technology to detect differentially expressed proteins (DEPs) in the brain tissues of benzene poisoning mice and initially explored the mechanisms of neurotoxicity of benzene poisoning.
Materials and methods
Animals acquisition and feeding
Thirty male C57BL/6J pathogen-free mice (6 weeks-of-age, 18–20 g) were purchased from the Animal Experiment Centre of our institution. All experimental animals were housed in a specific pathogen free (SPF) standard animal surrogate room with 12 h light/dark cycle, 21–24 °C of temperature, 40%–70% of humidity.
Animal treatment and sample collection
Thirty mice were randomly divided into two groups (fifteen mice in each group) and labelled as benzene poisoning group and control group. The method of establishing the animal model of benzene poisoning was based on the study of Li11 with some changes in the contamination dose of benzene. Benzene (Sigma-Aldrich, USA; ACS reagent, ≥99.0%) was diluted using peanut oil as the vehicle. After one week of adaptive feeding, mice in the benzene poisoning group were given benzene-peanut oil suspension by gavage (the dose of benzene was 2,000 mg/kg, and the volume of gavage was 10 mL/kg) for four consecutive weeks (once a day, six times one week). The control mice were given peanut oil by gavage, and the gavage dose were the same as the benzene poisoning group. Gavage was stopped after four weeks, the number of leukocytes, neutrophils, and blood platelets in mice orbital vein blood was measured by an automatic blood cell analyzer (BC-2800vet, Mindray, China) in the following two weeks (weekend of week 4 and week 5).
All benzene poisoning and control group mice were anaesthetized (1% pentobarbital, 50 mg/kg, intraperitoneal injection) and then executed by cervical dislocation at the same time period after the second blood index test completed (weekend of week 5). Mice heart, liver, brain and lung were taken and weighed, and organ index was calculated (organ index = organ weight/body weight × 100%). The whole brains of mice were extracted carefully and washed with ice-cold saline. Every brain tissue was cut along the coronal plane (the largest surface of the hippocampus) and divided into two parts. Half of the brain were stored at −80 °C for protein detection and the remaining brains were fixed in 10% phosphate buffered formalin.
Protein extraction and TMT labeling
The method of protein extraction and TMT labeling in this experiment was referenced from Xia et al.12 (1) The reaction solution (1.5% SDS/100 mM Tris–HCl, pH = 8.5) was added to brain samples and incubated at 95 °C for 10 min, followed by centrifugation of the supernatant. (2) TCA precipitation method was used to precipitate the proteins in the upper layer of the solution. The protein concentration was determined by the BCA method after re-dissolving the obtained protein precipitation by adding re-solution (8 M Urea/100 mM Tris-HCl, pH = 8.5). (3) An equal amount of protein was made up to the same volume, and 2-carboxyethyl and chloroacetamide were added and incubated at 37 °C for 1 h to carry out the reductive alkylation reaction. (4) Add 100 mM Tris-HCl solution to the reduced alkylated samples, dilute the concentration of Urea to less than 2 M, add trypsin at a 1:50 enzyme-to-protein mass ratio, and incubate at 37 °C with shaking overnight for digestion. (5) On the next day, TFA was added to terminate the enzyme digestion, and the supernatant was desalted by SDB-RPS desalting column, vacuum dried and frozen at −20 °C. (6) An aliquot of the sample was taken for TMT labelling. The labelled samples were mixed in aliquots and desalted using Sep-Pak C18. After vacuum drying, the mixed samples were separated hierarchically using high pH reverse chromatography and finally combined into 15 fractions. After vacuum drying, the samples were stored in a −80 °C refrigerator and prepared for on-line testing.
Mass spectrometric detection
Mass spectrometry data were collected using a Q Exactive HF mass spectrometer in tandem with an UltiMate 3,000 RSLCnano liquid phase in a liquid mass spectrometry system. The peptide samples were solubilised in the sample buffer, inhaled by an autosampler and separated on an analytical column (75 μm*25 cm, C18, 1.9 μm, 120 Å). An analytical gradient was established using two mobile phases (mobile phase A: 0.1% formic acid, 3% DMSO and mobile phase B: 0.1% formic acid, 3% DMSO, 80% ACN). The flow rate of the liquid phase was set to 300 nL/min. The mass spectra were acquired in DDA mode, with each scan cycle consisting of a full MS scan (R = 60 K, AGC = 3e6, max IT = 25 ms, scan range = 350–1,500 m/z), and 20 subsequent MS/MS scans (R = 45 K, AGC = 1e5, max IT = 80 ms). AGC = 1e5, max IT = 80 ms). The HCD collision energy was set to 32. the screening window for the quadrupole was set to 1.2 Da. the dynamic exclusion time for repeated ion acquisition was set to 24 s. The HCD collision energy was set to 32. the screening window for the quadrupole was set to 1.2 Da.
Protein identification and data analysis
Mass spectrometry data were searched by MaxQuant software (Max Planck Institute of Biochemistry, Germany), and the database search algorithm used by Andromeda. The database used for the search was the proteome reference database for mouse in uniprot online database (https://www.uniprot.org/). Relative protein expression was compared between the benzene poisoning group and control group to identify the DEPs. Proteins with a fold change (FC) > 1.2 (or < 1/1.2) and P-value < 0.05 were considered as DEPs.13,14 The obtained DEPs were imported into the STRING online database (https://cn.string-db.org) for functional interaction analysis. DAVID online database (https://david.ncifcrf.gov) was used for identified the gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) annotation. We used Cytoscape software to screen the key proteins and did protein-protein interaction (PPI) visualisation of the top 25 DEPs.
Immunoblotting
Three proteins, 2-hydroxyacylsphingosine 1-beta-galactosyltransferase (UGT8) (Polyclonal antibody, Proteintech, China), Apolipoprotein A-I (APOA1) (Polyclonal antibody, Proteintech, China) and Complement C3 (C3) (Proteintech, Polyclonal antibody, (Polyclonal antibody, Proteintech, China) were selected to validate the proteomics results by immunoblotting. We randomly selected three brain tissue samples each from the benzene poisoning and the control group for immunoblotting validation. Total protein in brain tissue samples was extracted and calculated by BCA method (Beyotime Biotechnology, China). Produced protein samples were used for separation by 10% SDS-PAGE gel electrophoresis, followed by transferring the proteins onto a nitrocellulose membrane. The membranes were incubated in a blocking buffer (containing 5% skimmed milk, 10 mM Tris-HCl, 150 mM NaCl, 0.1% Tween-20) for 2 h at room temperature. The membrane was then incubated with primary antibody at 4 °C overnight, washed the next day, and incubated with secondary antibody at 37 °C for 1 h, washed again. The bands were visualized with the ECL reagents.
Immunohistochemistry
We also chose the three proteins, UGT8, APOA1 and C3, for validation by immunohistochemistry, thus increasing the confidence of the TMT proteomics results. As with immunoblotting, we also randomly selected three brain tissue samples from each of the benzene poisoning and control groups for immunohistochemical validation. Brain tissue sections were incubated in the blocking buffer (containing 0.5% Triton×100 and 3% skim milk powder) for 30 min under room temperature. A drop of the prepared primary antibody was placed on the section and incubated at 4 °C overnight. Day two, the sections were removed and unbound primary antibody was washed off, followed by dropwise addition of secondary antibody and incubation for 30 min at room temperature. Finally, chromogenic agent was added to brain sections and counterstained with hematoxylin.
Statistical analysis
Data in this study were presented as mean ± SD and analyzed by SPSS 22.0 statistical software (IBM, USA). Data in different groups were analyzed by one-way analysis of variance (ANOVA) followed by the Tukey’s multiple comparison test. P-value < 0.05 was considered to be significant statistical difference.
Results
Animal model of benzene poisoning
Mice body weight and organ index
During the experimental period (four weeks) of contamination, three mice died in the benzene poisoning group, one died in the control group due to misoperation of gavage. About ten minutes after each gavage, mice in benzene poisoning group showed wet and erect coat, and persistent convulsions can be seen in some mice. We measured the body weight of mice once a week. The initial body weights of mice in each group were similar, body weights of mice in the benzene poisoning group increased at a lower rate than those of the control group in the four weeks (Fig. 1). We also measured the organ indices of the heart, lung, liver and brain of mice (Table 1). The results showed that except for heart, average organ indices of the lungs, liver and brain were greater in the benzene poisoning group than control group. However, there was no statistical difference between the benzene poisoning group and control group as mentioned above.
Fig. 1.
Changes in body weight of mice benzene exposure for four weeks.
Table 1.
Statistics of organ index in mice.
| Group | n | Weight (g) | Heart index (%) | Lung index (%) | Liver index (%) | Brain index (%) |
|---|---|---|---|---|---|---|
| Control | 14 | 20.77 ± 1.24 | 0.53 ± 0.039 | 0.82 ± 0.12 | 5.06 ± 0.12 | 2.09 ± 0.16 |
| Benzene poisoning | 12 | 18.75 ± 1.26* | 0.51 ± 0.044 | 0.91 ± 0.14 | 5.32 ± 0.41 | 2.20 ± 0.26 |
Note: “*” represents a statistically significant difference compared with control group, P < 0.05.
Blood index detection
Gavage was stopped for four weeks and the counts of leukocytes, neutrophils and blood platelets were measured twice in the following two weeks (week 4 and week 5). The results of mice leukocyte, neutrophil and blood platelet counts in benzene poisoning and control group were shown in Table 2. We found that the leukocytes and neutrophil counts at week 4 and week 5 were significantly lower in the benzene poisoning group than the control group (Fig. 2A and B), whereas the blood platelet counts at week 4 and week 5 showed no statistically different in the two groups (Fig. 2C).
Table 2.
Changes in blood indices after benzene exposure in mice.
| Blood index | Control | Benzene poisoning | ||
|---|---|---|---|---|
| week 4 | week 5 | week 4 | week 5 | |
| Leukocyte (×109) | 5.56 ± 1.06 | 5.44 ± 0.72 | 3.38 ± 0.59* | 3.45 ± 0.51* |
| Neutrophils (×109) | 1.39 ± 0.48 | 1.20 ± 0.40 | 0.86 ± 0.36* | 0.78 ± 0.29* |
| Blood platelet (×109) | 1536.1 ± 315.7 | 1517.5 ± 161.3 | 1729.0 ± 235.6 | 1682.8 ± 215.2 |
Note: “*” represents a statistically significant difference compared with control group, P < 0.05.
Fig. 2.
Mice leukocyte (A), neutrophil (B) and blood platelet (C) counts in week 4 and week 5. The number of cells was counted, “*” indicates P < 0.05 compared with the control group.
Histological observation
The results of HE staining showed that compared with the control group, the brain tissue in the benzene poisoning group showed local cerebral oedema and small vessel occlusion in cerebral white matter. We found that the nucleus of some neuronal cells in the hippocampal region of benzene poisoning mice were deeply stained, the cytoplasm was more basophilic, which seemed to be a tendency of neuronal apoptosis or necrosis (Fig. 3).
Fig. 3.
Histopathological observation of brain tissue in benzene poisoning and control group. (A and C) control group; (B and D) benzene poisoning group.
Identification of DEPs
Nine brain samples from each group were selected for TMT proteomic analysis to identify the DEPs. A total of 6,985 proteins were identified in this study. DEPs in each group for comparison were screened with FC > 1.2 (or < 1/1.2) and P-value < 0.05. Based on the above screening standard, we identified a total of 43 DEPs, of which 14 DEPs were significantly up-regulated and 29 DEPs significantly down-regulated (Table 3).
Table 3.
The DEPs in benzene poisoning group vs. control group of mice brain.
| Accession | Gene | Description | P-value | Regulation |
|---|---|---|---|---|
| Q9Z320 | Krt27 | Keratin, type I cytoskeletal 27 | 0.0394 | UP |
| Q4PZA2 | Ece1 | Endothelin-converting enzyme 1 | 0.0370 | UP |
| Q923U0 | Tom1l1 | TOM1-like protein 1 | 0.0149 | UP |
| Q9JIL5 | Tulp4 | Tubby-related protein 4 | 0.0488 | UP |
| Q80TA1 | Selenoi | Ethanolaminephosphotransferase 1 | 0.0189 | UP |
| Q9D0T1 | Snu13 | NHP2-like protein 1 | 0.0137 | UP |
| Q8BGF8 | Slc35d3 | Solute carrier family 35 member D3 | 0.0384 | UP |
| P97452 | Bop1 | Ribosome biogenesis protein BOP1 | 0.0315 | UP |
| Q9R257 | Hebp1 | Heme-binding protein 1 | 0.0020 | UP |
| Q64676 | Ugt8 | 2-hydroxyacylsphingosine 1-beta-galactosyltransferase | 0.0005 | UP |
| Q91WF7 | Fig4 | Polyphosphoinositide phosphatase | 0.0272 | UP |
| Q8CGK7 | Gnal | Guanine nucleotide-binding protein G(olf) subunit alpha | 0.0345 | UP |
| Q6IE26 | Ephx4 | Epoxide hydrolase 4 | 0.0222 | UP |
| Q6ZPK0 | Phf21a | PHD finger protein 21A | 0.0468 | UP |
| Q9JL60 | Gmeb1 | Glucocorticoid modulatory element-binding protein 1 | 0.0497 | DOWN |
| Q61702 | Itih1 | Inter-alpha-trypsin inhibitor heavy chain H1 | 0.0397 | DOWN |
| P07724 | Alb | Albumin | 0.0191 | DOWN |
| Q921I1 | Tf | Serotransferrin | 0.0066 | DOWN |
| Q01339 | Apoh | Beta-2-glycoprotein 1 | 0.0132 | DOWN |
| O08677 | Kng1 | Kininogen-1 | 0.0229 | DOWN |
| P09813 | Apoa2 | Apolipoprotein A-II | 0.0164 | DOWN |
| P17439 | Gba1 | Lysosomal acid glucosylceramidase | 0.0099 | DOWN |
| Q91WP6 | Serpina3n | Serine protease inhibitor A3N | 0.0210 | DOWN |
| P01942 | Hba | Hemoglobin subunit alpha | 0.0404 | DOWN |
| P29699 | Ahsg | Alpha-2-HS-glycoprotein | 0.0152 | DOWN |
| Q8CJ53 | Trip10 | Cdc42-interacting protein 4 | 0.0356 | DOWN |
| P01027 | C3 | Complement C3 | 0.0062 | DOWN |
| P47880 | Igfbp6 | Insulin-like growth factor-binding protein 6 | 0.0093 | DOWN |
| P33622 | Apoc3 | Apolipoprotein C-III | 0.0036 | DOWN |
| P41317 | Mbl2 | Mannose-binding protein C | 0.0102 | DOWN |
| P06728 | Apoa4 | Apolipoprotein A-IV | 0.0038 | DOWN |
| Q00623 | Apoa1 | Apolipoprotein A-I | 0.0152 | DOWN |
| P23953 | Ces1c | Carboxylesterase 1C | 0.0176 | DOWN |
| A2AJT4 | Pnisr | Arginine/serine-rich protein PNISR | 0.0333 | DOWN |
| P01872 | Ighm | Immunoglobulin heavy constant mu | 0.0463 | DOWN |
| Q9DBB9 | Cpn2 | Carboxypeptidase N subunit 2 | 0.0466 | DOWN |
| P52840 | Sult1a1 | Sulfotransferase 1A1 | 0.0293 | DOWN |
| Q61646 | Hp | Haptoglobin | 0.0300 | DOWN |
| Q91X72 | Hpx | Hemopexin | 0.0105 | DOWN |
| Q07456 | Ambp | Protein AMBP | 0.0066 | DOWN |
| P70665 | Siae | Sialate O-acetylesterase | 0.0199 | DOWN |
| Q8CF66 | Lamtor4 | Ragulator complex protein LAMTOR4 | 0.0486 | DOWN |
| P34928 | Apoc1 | Apolipoprotein C-I | 0.0346 | DOWN |
GO and KEGG pathway analysis of DEPs
The GO functional annotation and KEGG pathway analysis of DEPs using the DAVID (https://david.ncifcrf.gov) online website. The results showed that biological processes (BP) of the DEPs mainly include phospholipid efflux, lipoprotein metabolic process, cholesterol efflux, high-density lipoprotein particle remodeling and cholesterol metabolic process. Cellular components (CC) of the DEPs mainly include extracellular region, very-low-density lipoprotein particle, chylomicron, extracellular space and spherical high-density lipoprotein particle. Molecular functions (MF) of these DEPs mainly include lipase inhibitor activity, lipid binding, high-density lipoprotein particle receptor binding, phosphatidylcholine binding and phosphatidylcholine-sterol O-acyltransferase activator activity (Fig. 4). The KEGG pathway analysis of DEPs mainly include cholesterol metabolism, complement and coagulation cascades, african trypanosomiasis, PPAR signaling pathway, and vitamin digestion and absorption (Fig. 5).
Fig. 4.
GO analysis of DEPs using DAVID and gene ontology annotations. The ordinate in the figure represents the GO level explanatory information, including biological process (BP), cellular component (CC) and molecular function (MF).
Fig. 5.
Benzene poisoning group vs control group showed the results of the first 6 KEGG pathways with the most DEPs.
Analysis of key target proteins
To understand the specific mechanism of benzene poisoning, we further performed an association analysis of target proteins of DEPs. DEPs data were imported into STRING online database, the interaction score was set to 0.4, the PPI network interactions of DEPs were constructed and the corresponding “tsv” files were imported into Cytoscape software. Top 25 key target proteins associated with benzene poisoning were screened using the “cytohubba” algorithm in Cytoscape software. The PPI network of the key target proteins was shown in Fig. 6.
Fig. 6.
Protein-protein interaction networks of key target proteins in benzene poisoning group vs. control group.
Immunoblotting results
Above KEGG results showed that the main pathways of DEPs involve cholesterol metabolism, complement and coagulation cascades. We therefore screened three representative proteins (UGT8, APOA1 and C3) of KEGG for validation by immunoblotting. The protein expression level of UGT8 was significantly up regulated in benzene poisoning group (Fig. 7A and C), while that of APOA1 and C3 was significantly down regulated compared to the control group (Fig. 7A, B and D). The above results were consistent with the previous TMT proteomics screen.
Fig. 7.
The comparison of protein expression of C3, UGT8 and APOA1 by immunoblotting (A). The bands of C3 (B), UGT8 (C) and APOA1 (D) were semi-quantified by gray scale, “*” indicates P < 0.05 compared with the control group.
Immunohistochemistry results
To enhance the convincingness of the study, we re-validated the above three proteins UGT8, APOA1 and C3 by immunohistochemistry. The results showed that compared with control group, the expression of UGT8 significant increase, and APOA1 and C3 significant decrease in benzene poisoning group (Fig. 8). These findings were consistent with the results of TMT proteomics and western blot.
Fig. 8.
The comparison of protein expression of C3, UGT8 and APOA1 by immunohistochemistry. Original magnification of the figures was 200×. The positive expression cell of C3, UGT8 and APOA1 in brain tissue were counted, “*” indicates P < 0.05 compared with the control group.
Discussion
At present, we still know relatively little about the nervous system damage caused by benzene poisoning. Although some scholars have done preliminary research, its specific poisoning mechanism and diagnostic basis was still unclear.2 In this study, we established a mouse model of benzene poisoning and observed a significant decrease in leukocytes and neutrophils in benzene poisoning mice. We also observed some brain damage such as cerebral oedema, small vessel occlusion and suspected neuronal apoptosis or necrosis in benzene poisoning mice with HE staining. In this study, we focused on the molecular changes following neurological toxicity and used a TMT proteomic approach to identify DEPs in the brain of benzene poisoning, with the aim of being able to preliminarily investigate the mechanisms of neurological damage in benzene poisoning.
Through a KEGG analysis above, we found that compared with control group, DEPs in benzene poisoning group were mainly concentrated in cholesterol metabolism, complement and coagulation cascades, african trypanosomiasis, PPAR signaling pathway, and vitamin digestion and absorption. We also used western blot and immunohistochemistry technology validation for a number of poisoning related proteins (UGT8, APOA1, C3) and the results were consistent with proteomics.
UGT8 is a key enzyme in galactose ceramide biosynthesis, and studies have shown that UGT8 was closely associated with metastasis of many cancers. High expression of UGT8 often predicts a poorer prognosis for these cancers.15,16 Ji et al.17 found that UGT8 was selectively highly expressed in non-small cell lung cancer (NSCLC) and is associated with poor prognosis through the integration of the Cancer Genome Atlas, the Gene Expression Atlas, and the Genotype-Tissue Expression Database. He further found that silencing UGT8 impaired glycolysis and reduced malignancy in NSCLC in vitro and vivo experiments. Cao et al.18 found that UGT8 showed high expression in basal-like breast cancers and also had a poor prognosis. He further found that high expression of UGT8 promotes tumourigenesis, while knockdown of UGT8 inhibits tumourigenesis and metastasis. UGT8 has also been reported high expression in gastric cancer.19 Interestingly, the outcome of long-term chronic benzene intoxication is also tumour (leukaemia). Our results showed that UGT8 was highly expressed in benzene poisoning group, and it was worthwhile to further study whether it also plays an important role in the leukaemia caused by benzene. Thus, UGT8 may be one of the potential biological indicators of benzotoxicity.
APOA1 is mainly synthesised in the liver (80%) and small intestine (20%) in the form of pre-apolipoprotein A1(267 amino acids).20 The main functions of APOA1 are reverse cholesterol transport, anti-inflammatory and antioxidant effects as well as improvement of insulin resistance and lowering of blood glucose.21 Studies have shown that APOA1 was closely associated with the development of multiple diseases. Among lipoproteins, high-density lipoprotein (HDL) and its major protein component APOA1 were directly involved in the cholesterol efflux pathway in the brain. It has been shown that insufficient or dysfunctional brain HDL may lead to cerebrovascular dysfunction, neurodegeneration, or neurovascular instability.22 Dyslipidaemia was an important risk factor for cerebral infarction and dementia. Studies have shown that HDL has a significant improvement in cerebral infarction and dementia,23 and increasing HDL levels could protect neurons from damage.24 More, many studies showed that variations in the APOA1 gene might affect the function of the protein, which in turn affects cholesterol metabolism in the brain, leading to an increased risk of developing Alzheimer’s disease.22,25,26 Our results showed that APOA1 protein was significantly down-regulated in brain of mice in benzene poisoning group compared with the control group, and its related proteins APOA2, APOA4, APOC1, APOC3 and APOH were also significantly down-regulated. Combining the above theories and our experimental results, we speculate that benzene most likely affects the cholesterol metabolism pathway in the nervous system. Moreover, benzene toxicity has the potential to affect cognitive function in mice by reducing brain HDL levels. Therefore, APOA1 and its related apolipoproteins are the next step in our research in benzene poisoning.
C3, an important component of the body’s complement system, is widely found in blood, tissues and cell membranes.27,28 Liver is the most important source of complement molecules, and its main function is to be responsible for the immune regulation of the body. Under the conditions of injury, infection, oxidative stress, etc., the complement system is rapidly activated and exerts regulatory functions.29 Markiewski et al.30 studied the changes in the complement system after toxic liver injury. He found that complement activation products (C3a, C3b/iC3b) were produced in the serum of experimental mice after injection of CCl4 and demonstrated that complement activation was necessary for normal liver regeneration. Sun31 investigated the mechanism of complement changes in acute lung injury after paraquat poisoning and showed that early lung injury (24 h) showed a significant increase in the expression of complement proteins C1q and C3 in lung tissue. However, there was no further increase in the expression of C3 in lung tissue after 24 h of intoxication, and there was even a tendency for it to decrease. Zhang et al.32 examined the serum proteome of patients with benzene poisoning by using 2D-DIGE and MALDI-TOF-MS as a protein assay. He found that complement C3 were significantly up-regulated in patients with benzene poisoning, which may serve as biomarkers for early detection and diagnosis of benzene poisoning. The results of our experiments showed that the expression of C3 in the brain of mice in the benzene poisoning group was reduced, which may be related to the long-term toxic effects on the brain tissue, disrupting the immune regulation of the nervous system. Therefore, we speculate that complement C3 is responsively elevated early in the body in response to toxic stimuli, and that this expression gradually depletes and decreases in response to prolonged toxicity. The relationship between benzene poisoning and the complement system is also worthy of in-depth study, which may have an important role for the treatment of benzene poisoning.
However, there are still some shortcomings in our study. We used a gavage method to treat mice with benzene. The simulation of human poisoning environment through static room inhalation can make the model closer to clinical practice. As the inhalation time and concentration increase, the decrease in leukocyte and blood platelet count becomes more significant. However, this method suffers from the disadvantages of long modelling times and erratic absorption of toxins. The gavage and subcutaneous injection methods have a significant impact on leukocyte and blood platelets in a very short period as the concentration of benzene increases, and can meet the diagnostic criteria of benzene poisoning models earlier. However, these two modelling methods also have the drawback of being detached from reality.
It is also unfortunate that no behavioural tests were performed on the mice, which is another shortcoming of this study. Behavioural experiments could better assess the degree of neurological damage in mice. Therefore, in the follow-up study, we will use these DEPs as a starting point, combined with animal behavioural experiments as well as some special brain tissue staining, to deeply study the nervous system caused by benzene exposure.
Conclusion
In this study, we systematically investigated the expression of DEPs in mice brain of benzene poisoning model using TMT proteomics. The expression of some DEPs, such as UGT8, APOA1 and C3, may be useful for the prediction of benzene poisoning. However, the stability as well as the applicability of these proteins need further studies.
Contributor Information
Zhe Zheng, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, 263, Kaiyuan Avenue, Luoyang 471023, Henan, China.
Hongwei Li, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, 263, Kaiyuan Avenue, Luoyang 471023, Henan, China.
Zhenqian Zhang, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, 263, Kaiyuan Avenue, Luoyang 471023, Henan, China.
Xiandun Zhai, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, 263, Kaiyuan Avenue, Luoyang 471023, Henan, China.
Haojie Qin, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, 263, Kaiyuan Avenue, Luoyang 471023, Henan, China.
Author contributions
Zhe Zheng (Conceptualization, performing the experiments, and writing—original draft), Hongwei Li and Zhenqian Zhang (Performing the experiments and data analysis), and Xiandun Zhai and Haojie Qin (Supervision and writing—review & editing).
Funding
None.
Conflict of interest statement: No conflict of competing interest exits in the manuscript, and manuscript is approved by all authors for publication.
Data accessibility
The mass spectrometry proteomics data have been deposited to the ProteomeXchange via the PRIDE database (http://www.ebi.ac.uk/pride) by corresponding author with the dataset identifier PXD046028.
References
- 1. Ji Y, Gao F, Wu Z, Li L, Li D, Zhang H, Zhang Y, Gao J, Bai Y, Li H. A review of atmospheric benzene homologues in China: characterization, health risk assessment, source identification and countermeasures. J Environ Sci (China). 2020:95:225–239. [DOI] [PubMed] [Google Scholar]
- 2. Galbraith D, Gross SA, Paustenbach D. Benzene and human health: a historical review and appraisal of associations with various diseases. Crit Rev Toxicol. 2010:40(sup2):1–46. [DOI] [PubMed] [Google Scholar]
- 3. Falzone L, Marconi A, Loreto C, Franco S, Spandidos DA, Libra M. Occupational exposure to carcinogens: benzene, pesticides and fibers (Review). Mol Med Rep. 2016:14(5):4467–4474. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Robert S. Leukemia and benzene. Int J Environ Res Public Health. 2012:9(8):2875–2893. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Lu PCW, Shahbaz S, Winn LM. Benzene and its effects on cell signaling pathways related to hematopoiesis and leukemia. J Appl Toxicol. 2020:40(8):1018–1032. [DOI] [PubMed] [Google Scholar]
- 6. Chan C-C, Shie R-H, Chang T-Y, Tsai D-H. Workers' exposures and potential health risks to air toxics in a petrochemical complex assessed by improved methodology. Int Arch Occup Environ Health. 2006:79(2):135–142. [DOI] [PubMed] [Google Scholar]
- 7. Haseeb AK. Benzene's toxicity: a consolidated short review of human and animal studies. Hum Exp Toxicol. 2007:26(9):677–685. [DOI] [PubMed] [Google Scholar]
- 8. Iannaccone A, Cicchella G. Histological changes in the anterior pituitary gland of rats intoxicated with benzene. J Endocrinol. 1958:17(4):444–448. [DOI] [PubMed] [Google Scholar]
- 9. van Wijngaarden E, Stewart PA. Critical literature review of determinants and levels of occupational benzene exposure for United States community-based case-control studies. Appl Occup Environ Hyg. 2003:18(9):678–693. [DOI] [PubMed] [Google Scholar]
- 10. Hu J, Yu E, Liao Z. Changes in cognitive function and related brain regions in chronic benzene poisoning: a case report. Ann Transl Med. 2021:9(1):81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Li H, Li D, He Z, Fan J, Li Q, Liu X, Guo P, Zhang H, Chen S, Li Q, et al. The effects of Nrf2 knockout on regulation of benzene-induced mouse hematotoxicity. Toxicol Appl Pharmacol. 2018:358:56–67. [DOI] [PubMed] [Google Scholar]
- 12. Xia Y, Huang X, Mo L, Wang C, Fan W, Huang H. TMT-based proteomics analysis of the cerebral cortex of TauT knockout rats. Proteome Sci. 2022:20(1):6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Zhao C, Zheng Z, Zhu S, Zhang L, Zhang P, Xiong H, Li Y, Zhu Y, Zhao M, Li J. iTRAQ and PRM-based comparative proteomic profiling of the hippocampus in rat models of epilepsy. J Integr Neurosci. 2023:22(1):21. [DOI] [PubMed] [Google Scholar]
- 14. Cui Y, He L, Yang C-Y, Ye Q. iTRAQ and PRM-based quantitative proteomics in early recurrent spontaneous abortion: biomarkers discovery. Clin Proteomics. 2019:16(1):36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Liu W, Li J, Zhao R, Lu Y, Huang P. The uridine diphosphate (UDP)-glycosyltransferases (UGTs) superfamily: the role in tumor cell metabolism. Front Oncol. 2022:12:1088458. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Meech R, Hu DG, McKinnon RA, Mubarokah SN, Haines AZ, Nair PC, Rowland A, Mackenzie PI. The UDP-glycosyltransferase (UGT) superfamily: new members, new functions, and novel paradigms. Physiol Rev. 2019:99(2):1153–1222. [DOI] [PubMed] [Google Scholar]
- 17. Ji J, Xie M, Qian Q, Xu Y, Shi W, Chen Z, Ren D, Liu W, He X, Lv M, et al. SOX9-mediated UGT8 expression promotes glycolysis and maintains the malignancy of non-small cell lung cancer. Biochem Biophys Res Commun. 2022:587:139–145. [DOI] [PubMed] [Google Scholar]
- 18. Cao Q, Chen X, Wu X, Liao R, Huang P, Tan Y, Wang L, Ren G, Huang J, Dong C. Inhibition of UGT8 suppresses basal-like breast cancer progression by attenuating sulfatide-αVβ5 axis. J Exp Med. 2018:215(6):1679–1692. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Xiong Z, Lin Y, Yu Y, Zhou X, Fan J, Rog CJ, Cai K, Wang Z, Chang Z, Wang G, et al. Exploration of lipid metabolism in gastric cancer: a novel prognostic genes expression profile. Front Oncol. 2021:11:712746. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Cochran BJ, Ong K-L, Manandhar B, Rye K-A. APOA1: a protein with multiple therapeutic functions. Curr Atheroscler Rep. 2021:23(3):11. [DOI] [PubMed] [Google Scholar]
- 21. Bhale AS, Venkataraman K. Leveraging knowledge of HDLs major protein ApoA1: structure, function, mutations, and potential therapeutics. Biomed Pharmacother. 2022:154:113634. [DOI] [PubMed] [Google Scholar]
- 22. Bahrami A, Barreto GE, Lombardi G, Pirro M, Sahebkar A. Emerging roles for high-density lipoproteins in neurodegenerative disorders. Biofactors. 2019:45(5):725–739. [DOI] [PubMed] [Google Scholar]
- 23. Singh-Manoux A, Gimeno D, Kivimaki M, Brunner E, Marmot MG. Low HDL cholesterol is a risk factor for deficit and decline in memory in midlife: the Whitehall II study. Arterioscler Thromb Vasc Biol. 2008:28(8):1556–1562. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Panza F, D'Introno A, Colacicco AM, Capurso C, Pichichero G, Capurso SA, Capurso A, Solfrizzi V. Lipid metabolism in cognitive decline and dementia. Brain Res Rev. 2006:51(2):275–292. [DOI] [PubMed] [Google Scholar]
- 25. Lu H, Wang B, Liu Y, Wang D, Fields L, Zhang H, Li M, Shi X, Zetterberg H, Li L. DiLeu isobaric Labeling coupled with limited proteolysis mass spectrometry for high-throughput profiling of protein structural changes in Alzheimer's disease. Anal Chem. 2023:95(26):9746–9753. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Pillai JA, Bena J, Bekris L, Kodur N, Kasumov T, Leverenz JB, Kashyap SR, on behalf of the Alzheimer’s Disease Neuroimaging Initiative . Metabolic syndrome biomarkers relate to rate of cognitive decline in MCI and dementia stages of Alzheimer's disease. Alzheimers Res Ther. 2023:15(1):54. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Zarantonello A, Revel M, Grunenwald A, Roumenina LT. C3-dependent effector functions of complement. Immunol Rev. 2023:313(1):120–138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Delanghe JR, Speeckaert R, Speeckaert MM. Complement C3 and its polymorphism: biological and clinical consequences. Pathology. 2014:46(1):1–10. [DOI] [PubMed] [Google Scholar]
- 29. Copenhaver M, Yu CY, Hoffman RP. Complement components, C3 and C4, and the metabolic syndrome. Curr Diabetes Rev. 2019:15(1):44–48. [DOI] [PubMed] [Google Scholar]
- 30. Markiewski MM, Mastellos D, Tudoran R, DeAngelis RA, Strey CW, Franchini S, Wetsel RA, Erdei A, Lambris JD. C3a and C3b activation products of the third component of complement (C3) are critical for normal liver recovery after toxic injury. J Immunol. 2004:173(2):747–754. [DOI] [PubMed] [Google Scholar]
- 31. Sun S, Wang H, Zhao G, An Y, Guo Y, du L, Song H, Qiao F, Yu H, Wu X, et al. Complement inhibition alleviates paraquat-induced acute lung injury. Am J Respir Cell Mol Biol. 2011:45(4):834–842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Zhang Z, Li P, Lin D, Wang D, Zhang Y. Proteome analysis of the potential serum biomarkers for chronic benzene poisoning. Environ Toxicol Pharmacol. 2018:60:157–164. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The mass spectrometry proteomics data have been deposited to the ProteomeXchange via the PRIDE database (http://www.ebi.ac.uk/pride) by corresponding author with the dataset identifier PXD046028.