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Gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium (VI)
Accepted Manuscript Title: Gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium(VI) Author: Guiping Hu Jiaxing Liu Yongming Zhang Pai Zheng Lele Wang Lin Zhao Huadong Xu Zhangjian Chen Tiancheng Wang Guang Jia PII: DOI: Reference:
S0378-4274(16)33289-1 http://dx.doi.org/doi:10.1016/j.toxlet.2016.10.015 TOXLET 9625
To appear in:
Toxicology Letters
Received date: Revised date: Accepted date:
29-8-2016 17-10-2016 24-10-2016
Please cite this article as: Hu, Guiping, Liu, Jiaxing, Zhang, Yongming, Zheng, Pai, Wang, Lele, Zhao, Lin, Xu, Huadong, Chen, Zhangjian, Wang, Tiancheng, Jia, Guang, Gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium(VI).Toxicology Letters http://dx.doi.org/10.1016/j.toxlet.2016.10.015 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Gene Expression Profiling and Bioinformatics Analysis in 16HBE Cells Treated by Chromium (VI)
Guiping Hua, Jiaxing Liua, Yongming Zhangb, Pai Zhengc, Lele Wanga, Lin Zhaoa, Huadong Xua, Zhangjian Chena, Tiancheng Wangd,* ##Email##[email protected]##/Email##, Guang Jiaa,** ##Email##[email protected]##/Email## a. Department of Occupational and Environmental Health Science, School of Public Health, Peking University, Beijing 100191, China b. Department of Occupational and Environmental Health Science, School of Public Health, Baotou Medical College, Baotou, Inner Mongolia Autonomous Region 014030, China c. Editorial Department of Chinese Journal of Preventive Medicine, Chinese Medical Association, Beijing 100710, China d. Department of Clinical Laboratory, Third Hospital of Peking University, Beijing 100191, China, Beijing 100191, China
Tiancheng Wang, Department of Clinical Laboratory, Third Hospital of Peking
University, Beijing 100191, China, Beijing 100191, China. Tel.: +86 10 8280 2333; fax: +86 10 8280 2333.*
Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China. Tel.: +86 10 8280 2333; fax: +86 10 8280 2333.
Highlights：
Gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium(VI)compound was performed.
Cr(VI) toxicity effects may involve in oxidative stress, inflammation, energy metabolism, protein synthesis endocytosis, ion binding, DNA binding and metabolism, cell morphogenesis, cell cycle regulation, autophagy, apoptosis, cell death, and carcinogenesis by some specific pathway
Some significantly differential expression genes can be used as potential biomarkers of Cr(VI) exposure.
Abstract Hexavalent chromium [Cr(VI)] compounds are widely used in industry and agriculture and are also ubiquitous environmental contaminant which are recognized as one kind of carcinogen, mutagen and teratogen towards humans and animals. To determined the Cr(VI) toxicity effects, gene expression profile can be meaningful for discovering underlying mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. In the current study, gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium (VI) compound was performed. The MTT assay was done to determine the optimal Cr (VI) treated concentration and time. The mRNA expression profile was performed using Arraystar Microarray V3.0 at 10.00 μM Cr(VI). RT-qPCR was applied to verify some interested significantly altered genes at different treatment groups. Comprehensive analysis including biological processes, GO ontology network, pathway network analysis and gene-gene network analysis was conducted to identify the related biological processes, signal pathway and critical genes. It was found that Cr(VI) could induce reduced cells viability and alter gene expression profile of human bronchial epithelial cells. 2273 significantly differential expressed genes formed a complex network and some expressions changed in a Cr(VI) concentration dependent manner. In conclusion, Cr(VI) toxicity effects may involve in oxidative stress, inflammation, energy metabolism, protein synthesis endocytosis, ion binding, DNA binding and metabolism, cell morphogenesis, cell cycle regulation, autophagy, apoptosis, cell death, and carcinogenesis by some specific pathway. Meanwhile, some significantly differential expression genes can be used as potential biomarkers of Cr(VI) exposure. Keywords: Hexavalent chromium Cr (VI); Gene expression profile; Microarray analysis; Bioinformatics analysis
1. Introduction Hexavalent chromium [Cr(VI)] and its compounds have been recognized to be carcino genic (IARC, 1990) based on numerous observations in occupational epidemiology studies (Rosenman and Stanbury, 1996). Since the widespread use of chromium in industries and agriculture, amounts of chromium slag and chromium waste water were discharged into environment which induced increasing concern about the environmental influence and health effects of Cr(VI) (Rosenman and Stanbury, 1996). Except a higher lung cancer risk, workers in chromate production, plating, pigments, welding and leather tanning industries historically exposed to Cr(VI) also suffered from an increased risk of immune disorders
S0378-4274(16)33289-1 http://dx.doi.org/doi:10.1016/j.toxlet.2016.10.015 TOXLET 9625
To appear in:
Toxicology Letters
Received date: Revised date: Accepted date:
29-8-2016 17-10-2016 24-10-2016
Please cite this article as: Hu, Guiping, Liu, Jiaxing, Zhang, Yongming, Zheng, Pai, Wang, Lele, Zhao, Lin, Xu, Huadong, Chen, Zhangjian, Wang, Tiancheng, Jia, Guang, Gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium(VI).Toxicology Letters http://dx.doi.org/10.1016/j.toxlet.2016.10.015 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Tiancheng Wang, Department of Clinical Laboratory, Third Hospital of Peking
University, Beijing 100191, China, Beijing 100191, China. Tel.: +86 10 8280 2333; fax: +86 10 8280 2333.
Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China. Tel.: +86 10 8280 2333; fax: +86 10 8280 2333.
Highlights：
Gene expression profiling and bioinformatics analysis in 16HBE cells treated by chromium(VI)compound was performed.
Cr(VI) toxicity effects may involve in oxidative stress, inflammation, energy metabolism, protein synthesis endocytosis, ion binding, DNA binding and metabolism, cell morphogenesis, cell cycle regulation, autophagy, apoptosis, cell death, and carcinogenesis by some specific pathway
Some significantly differential expression genes can be used as potential biomarkers of Cr(VI) exposure.
1. Introduction Hexavalent chromium [Cr(VI)] and its compounds have been recognized to be carcino genic (IARC, 1990) based on numerous observations in occupational epidemiology studies (Rosenman and Stanbury, 1996). Since the widespread use of chromium in industries and agriculture, amounts of chromium slag and chromium waste water were discharged into environment which induced increasing concern about the environmental influence and health effects of Cr(VI) (Rosenman and Stanbury, 1996). Except a higher lung cancer risk, workers in chromate production, plating, pigments, welding and leather tanning industries historically exposed to Cr(VI) also suffered from an increased risk of immune disorders
(Beaver et al., 2009), stomach (Welling et al., 2015) and intestinal (Thompson et al., 2014), liver (Patlolla et al., 2009) and kidney damage (Wang et al., 2011). However, the biological mechanisms of multi-system disorders and genetic damage of Cr(VI) exposure remain unknown. Chromate Cr(VI) closely resembles sulfate (SO42−) and thus could enter cells via an anion carrier (Buttner and Beyersmann, 1985). As a strong oxidant, Cr(VI) can produce a series of reactive oxygen species (ROS) and undergo a series of metabolic reductions to form reactive Cr(V) and Cr(IV) intermediates as well as the final stable metabolite Cr(III), which could induce oxidative stress or genetic damage (Myers, 2012). It is extensively accepted that genetic lesions induced by Cr(VI) are associated with ROS, Cr-DNA adducts, oxidized bases, DNA-protein crosslinks, energy metabolism and DNA strand breaks which dominate the underlying mechanisms of apoptosis and carcinogenesis (Myers, 2012). Our previous studies (Li et al., 2014) have found that 8-OHdG and micronucleus (MN) in blood have a positive correlation with blood Cr(VI) and might be used as potential early genetic damage biomarkers. Many studies revealed that the intricate genetic damage repair pathways were activated upon DNA damage and played a critical role in the repair of Cr(VI)-induced DNA strand breaks (Halasova et al., 2012; Reynolds et al., 2004; Zhitkovich et al., 2005). What’s more, the cell apoptosis related cell cycle regulation pathways are involved in the DNA damage induced by Cr(VI) exposure (Hu et al., 2016). However, more evidences on toxicity effects of Cr(VI) exposure and bioinformatics analysis method are still required. The alternative to toxic effects involved in Cr(VI) exposure can be associated with oxidative stress, DNA damage, DNA repair, apoptosis elements acting and so on via a variety of genes (Nigam et al., 2014). A marked gene expression profile or signal regulation pathway induced by Cr(VI) could contribute to a comprehensive insight into toxicity effects of Cr(VI) exposure. The Cr(VI)-altered cellular gene expression profile could be treated as the possible molecular based navigation of the onset or progress of various effects (Nigam et al., 2014). Previous studies have shown altered genes expression that a number of genes were changed in response to acute or high Cr(VI) exposure to human cells (Andrew et al., 2003; Ye and Shi, 2001). However, the Cr(VI) biological activities are complicated and remained to be fully investigated. To better understand the characteristic alerted genes and mechanisms of Cr(VI) toxic effect, microarray analysis was used to identify the mRNA expression profile for Cr (VI) treated 16 HBE cells. Besides, the real-time quantitative polymerase chain reaction (RT-qPCR) was used to verify some interested significantly altered genes identified by gene microarray. Bioinformatics analysis including go ontology net analysis, pathway analysis and gene-gene-net analysis were also performed to analyze the possible biological processes, signal pathway and critical genes and mechanisms of Cr(VI) exposure effects.
2. Materials and methods 2.1 Cell culture and treatment condition and time
Human bronchial epithelial cell lines (16HBE cells) were purchased from the tumor cell library of Chinese Academy of Cell Resource Center (Shanghai, China). 16HBE cells were cultured in DMEM supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 μg/mL streptomycin, and maintained at 37 ℃ in a humidified atmosphere containing 5% CO2 and 95% air. Depending on the experiment design, 1×104 16 HBE cells were treated in 96-well plates with dichromate (Cr2O72−) (Sigma, USA) stoke solution diluted in cell culture medium at various concentrations: 0.00, 0.63, 1.23, 2.50, 5.00, 10.00, 20.00, 50.00 and 100.00 μM for 12, 24 and 48 h. Then, the other treatment does were considered by the following experiment. All controls were exposed to medium with the same volume as Cr(VI) stoke solution but replaced by ddH2O (Sigma, USA) and underwent the same condition as experimental group. 2.2 RNA isolation and mRNA gene expression profile analysis Accroding to the experiment design, 1.2×106 16 HBE cells were treated in 6-well plates with various Cr(VI) concentrations. Then, the total RNA was extracted using TRIzol reagent (InvitrogenTM, USA) according to the manufacturer' s protocol. The NanoDrop 2000c spectrophotometers (Thermo, USA) were used to measure the absorbance at 260 nm (A260) and at 280 nm (A280) and evaluate the RNA integrity and concentration. RNA integrity was assessed by standard denaturing agarose gel electrophoresis. RNA was amplified and transcribed into cDNA utilizing a random priming method, and sample labeling and array hybridization were performed according to the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technology) with minor modifications by Arraystar Human gene Microarray V3.0 (8×60 K, Arraystar Inc., Rockville, MD, USA) which can detect 26,109 coding transcripts. 2.3 Cell proliferation and cell viability rate MTT assay was used to analyze the cell viability and cell proliferation (Mosmann, 1983). Approximately 5×103 cells were plated in each well of 96-well plate to substrate for 24 h. The cells were then exposed to 0.00, 0.63, 1.23, 2.50, 5.00, 10.00, 50.00 and 100.00 μM Cr(VI) for 12, 24 or 48 h. Finally, the absorbance was measured at 492 nm on Microplate Reader (Thermo Fisher, USA). Each sample was repeated three times in triplicate parallel on separate cell cultures (n≥3 for cytotoxicity). The reduction in cell viability was expressed as a percent normalized to non-treated control cells. As described in our previous work (Hu et al., 2016), to detect the cell proliferation and cell viability rate, all the groups were analyzed by SPSS software to calculate the IC50 for Cr(VI) treatment concentration and time. 2.4 Differential expressed gene analysis To analyses the differential expressed gene, six samples were send to do Microarray including three control samples and three treated samples. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed with using the GeneSpring
GX v12.1 software package (Agilent Technologies). After quantile normalization of the raw data, mRNAs that at least 3 out of 6 samples have flags in Present or Marginal (``All Targets Value'') were chosen for further data analysis. The criterias of up-regulation and down-regulation of differential expressed genes were fold change >2 and fold change <0.5 respectively. Differential expressed mRNAs were identified through Fold Change filtering and the statistical significance of differential expressed mRNAs between the two groups were identified through random variance model Hierarchical Clustering and combined analysis were performed using homemade scripts. These p values were considered statistically significant if they were <0.05. 2.5 Validation of critical differential expressed gene The real-time Quantitative polymerase chain reaction (RT-qPCR) was used to verify the differential expression model profiles identified by gene Microarray. Because of high test fee, only some critical differential expressed genes were detected. The primers (Supplementary Table 1) of these genes were designed by the Primer-Blast (https://www.ncbi.nlm.nih.gov/tools/primer-blast). The relative quantification was performed using the 2−ΔΔCt by PCR Master Mix for SYBR Green assays (Vazyme, USA) on Real Time qPCR system (CFX-96, Bio-Rad Company, USA). Each gene per individual analyzed was performed in triplicate parallel dishes (n≥3 for RT-qPCR), and genes expression data was normalized to GAPDH. 2.6 Gene ontology analysis Gene ontology analysis was applied to analyze the biological process, cellular component and molecular function of the found differential expression genes according to the Gene ontology project (Ashburner et al., 2000). Fisher’s exact test was used to find if there were actually more overlaps than it would be expected by chance between the differential expression genes list and the GO annotation list. The p-value<0.05 denoted the significance of GO terms enrichment in the differential expression genes. The interaction net of these significant GOs was mapped to summarize the functional interactions of differential expression genes. 2.7 Pathway-net analysis Pathway analysis was applied to analyze the interaction net of the significant pathways of differential expression genes based on the KEGG database (http://www.kegg.jp/kegg/pathway.html) (Yi et al., 2006). KEGG analysis (KEGG data version: Release 70.1, June 1, 2014) was used for discovering the relation that was not easily visible from the changes of individual genes. Fisher's exact test was made to select the significant pathway and Fold change >2.0 and <0.5 were defined as up-regulation and down-regulation respectively for further analysis. The p-value <0.05 denotes the significance of the Pathway correlated to the conditions. The lower the p-value, the more significant is the Pathway. To summarize the pathway interaction of differential expression genes and find out the reason how certain pathway was activated, the interaction net of the
significant pathway of the differential expression genes was mapped to integrate the relationship pathway by outlining the interactions of related genes. 2.8 Gene-gene network analysis To build a gene–gene network, the interaction network was constructed in the STRING 10.0 (http://string-db.org/) according to the values among the differential expressed mRNAs and their interactions. STRING 10.0 is a resource to explore the known and predicted interactions of chemicals and protein-coding. To investigate the global network, the most important nodes were computationally identified by selecting up-expression and down-regulation of the differential expressed mRNAs. The parameters of required confidence (score) and interactors were set as medium confidence, no more than 10 interactors, respectively. p<0.05 was considered statistically significant and gene interactions could then be drawn based on the data. All functions encoded by these genes were found in gene database (http://www.ncbi.nlm.nih.gov/gene/).
3. Result 3.1 Cell viability rate and does As was shown in Fig. 1, the cell viability rate decreased significantly in a concentration dependent manner in all treatment doses after treating with Cr(VI) for 12, 24 and 48 h. The Student-Newman-Keuls( S-N-K ) test was used to find the difference of cell viability rate between control groups and treated groups. It was observed that with the time going and concentration rising, the Cr(VI) effects increased gradually. And when treated with 0.63 μM for 12 h, the experiment group 16HB cells began to show a significantly lower cell viability rate as compared with that in the control group Based on the IC50 value for Cr(VI), and the chromium concentration in workers’ blood from our previous occupational epidemiological investigation and findings (Hu et al., 2016; Li et al., 2015), the gene expression profile was performed at 10.00 μM Cr(VI) and the RT-qPCR at a variable treatment doses set to 0.00, 0.63, 1.23, 2.50, 5.00, and 10.00 μM. The treatment time was determined for 24 h. Note: The cell viability rate of 16HBE cells compared to controls following 12, 24 and 48 h treatment with different concentrations of Cr(VI) by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
2.1 Cell culture and treatment condition and time
Human bronchial epithelial cell lines (16HBE cells) were purchased from the tumor cell library of Chinese Academy of Cell Resource Center (Shanghai, China). 16HBE cells were cultured in DMEM supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 μg/mL streptomycin, and maintained at 37 ℃ in a humidified atmosphere containing 5% CO2 and 95% air. Depending on the experiment design, 1×104 16 HBE cells were treated in 96-well plates with dichromate (Cr2O72−) (Sigma, USA) stoke solution diluted in cell culture medium at various concentrations: 0.00, 0.63, 1.23, 2.50, 5.00, 10.00, 20.00, 50.00 and 100.00 μM for 12, 24 and 48 h. Then, the other treatment does were considered by the following experiment. All controls were exposed to medium with the same volume as Cr(VI) stoke solution but replaced by ddH2O (Sigma, USA) and underwent the same condition as experimental group. 2.2 RNA isolation and mRNA gene expression profile analysis Accroding to the experiment design, 1.2×106 16 HBE cells were treated in 6-well plates with various Cr(VI) concentrations. Then, the total RNA was extracted using TRIzol reagent (InvitrogenTM, USA) according to the manufacturer' s protocol. The NanoDrop 2000c spectrophotometers (Thermo, USA) were used to measure the absorbance at 260 nm (A260) and at 280 nm (A280) and evaluate the RNA integrity and concentration. RNA integrity was assessed by standard denaturing agarose gel electrophoresis. RNA was amplified and transcribed into cDNA utilizing a random priming method, and sample labeling and array hybridization were performed according to the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technology) with minor modifications by Arraystar Human gene Microarray V3.0 (8×60 K, Arraystar Inc., Rockville, MD, USA) which can detect 26,109 coding transcripts. 2.3 Cell proliferation and cell viability rate MTT assay was used to analyze the cell viability and cell proliferation (Mosmann, 1983). Approximately 5×103 cells were plated in each well of 96-well plate to substrate for 24 h. The cells were then exposed to 0.00, 0.63, 1.23, 2.50, 5.00, 10.00, 50.00 and 100.00 μM Cr(VI) for 12, 24 or 48 h. Finally, the absorbance was measured at 492 nm on Microplate Reader (Thermo Fisher, USA). Each sample was repeated three times in triplicate parallel on separate cell cultures (n≥3 for cytotoxicity). The reduction in cell viability was expressed as a percent normalized to non-treated control cells. As described in our previous work (Hu et al., 2016), to detect the cell proliferation and cell viability rate, all the groups were analyzed by SPSS software to calculate the IC50 for Cr(VI) treatment concentration and time. 2.4 Differential expressed gene analysis To analyses the differential expressed gene, six samples were send to do Microarray including three control samples and three treated samples. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed with using the GeneSpring
GX v12.1 software package (Agilent Technologies). After quantile normalization of the raw data, mRNAs that at least 3 out of 6 samples have flags in Present or Marginal (``All Targets Value'') were chosen for further data analysis. The criterias of up-regulation and down-regulation of differential expressed genes were fold change >2 and fold change <0.5 respectively. Differential expressed mRNAs were identified through Fold Change filtering and the statistical significance of differential expressed mRNAs between the two groups were identified through random variance model Hierarchical Clustering and combined analysis were performed using homemade scripts. These p values were considered statistically significant if they were <0.05. 2.5 Validation of critical differential expressed gene The real-time Quantitative polymerase chain reaction (RT-qPCR) was used to verify the differential expression model profiles identified by gene Microarray. Because of high test fee, only some critical differential expressed genes were detected. The primers (Supplementary Table 1) of these genes were designed by the Primer-Blast (https://www.ncbi.nlm.nih.gov/tools/primer-blast). The relative quantification was performed using the 2−ΔΔCt by PCR Master Mix for SYBR Green assays (Vazyme, USA) on Real Time qPCR system (CFX-96, Bio-Rad Company, USA). Each gene per individual analyzed was performed in triplicate parallel dishes (n≥3 for RT-qPCR), and genes expression data was normalized to GAPDH. 2.6 Gene ontology analysis Gene ontology analysis was applied to analyze the biological process, cellular component and molecular function of the found differential expression genes according to the Gene ontology project (Ashburner et al., 2000). Fisher’s exact test was used to find if there were actually more overlaps than it would be expected by chance between the differential expression genes list and the GO annotation list. The p-value<0.05 denoted the significance of GO terms enrichment in the differential expression genes. The interaction net of these significant GOs was mapped to summarize the functional interactions of differential expression genes. 2.7 Pathway-net analysis Pathway analysis was applied to analyze the interaction net of the significant pathways of differential expression genes based on the KEGG database (http://www.kegg.jp/kegg/pathway.html) (Yi et al., 2006). KEGG analysis (KEGG data version: Release 70.1, June 1, 2014) was used for discovering the relation that was not easily visible from the changes of individual genes. Fisher's exact test was made to select the significant pathway and Fold change >2.0 and <0.5 were defined as up-regulation and down-regulation respectively for further analysis. The p-value <0.05 denotes the significance of the Pathway correlated to the conditions. The lower the p-value, the more significant is the Pathway. To summarize the pathway interaction of differential expression genes and find out the reason how certain pathway was activated, the interaction net of the
significant pathway of the differential expression genes was mapped to integrate the relationship pathway by outlining the interactions of related genes. 2.8 Gene-gene network analysis To build a gene–gene network, the interaction network was constructed in the STRING 10.0 (http://string-db.org/) according to the values among the differential expressed mRNAs and their interactions. STRING 10.0 is a resource to explore the known and predicted interactions of chemicals and protein-coding. To investigate the global network, the most important nodes were computationally identified by selecting up-expression and down-regulation of the differential expressed mRNAs. The parameters of required confidence (score) and interactors were set as medium confidence, no more than 10 interactors, respectively. p<0.05 was considered statistically significant and gene interactions could then be drawn based on the data. All functions encoded by these genes were found in gene database (http://www.ncbi.nlm.nih.gov/gene/).
3. Result 3.1 Cell viability rate and does As was shown in Fig. 1, the cell viability rate decreased significantly in a concentration dependent manner in all treatment doses after treating with Cr(VI) for 12, 24 and 48 h. The Student-Newman-Keuls( S-N-K ) test was used to find the difference of cell viability rate between control groups and treated groups. It was observed that with the time going and concentration rising, the Cr(VI) effects increased gradually. And when treated with 0.63 μM for 12 h, the experiment group 16HB cells began to show a significantly lower cell viability rate as compared with that in the control group Based on the IC50 value for Cr(VI), and the chromium concentration in workers’ blood from our previous occupational epidemiological investigation and findings (Hu et al., 2016; Li et al., 2015), the gene expression profile was performed at 10.00 μM Cr(VI) and the RT-qPCR at a variable treatment doses set to 0.00, 0.63, 1.23, 2.50, 5.00, and 10.00 μM. The treatment time was determined for 24 h. Note: The cell viability rate of 16HBE cells compared to controls following 12, 24 and 48 h treatment with different concentrations of Cr(VI) by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
2.3 Cell proliferation and cell viability rate MTT assay was used to analyze the cell viability and cell proliferation (Mosmann, 1983). Approximately 5×103 cells were plated in each well of 96-well plate to substrate for 24 h. The cells were then exposed to 0.00, 0.63, 1.23, 2.50, 5.00, 10.00, 50.00 and 100.00 μM Cr(VI) for 12, 24 or 48 h. Finally, the absorbance was measured at 492 nm on Microplate Reader (Thermo Fisher, USA). Each sample was repeated three times in triplicate parallel on separate cell cultures (n≥3 for cytotoxicity). The reduction in cell viability was expressed as a percent normalized to non-treated control cells. As described in our previous work (Hu et al., 2016), to detect the cell proliferation and cell viability rate, all the groups were analyzed by SPSS software to calculate the IC50 for Cr(VI) treatment concentration and time. 2.4 Differential expressed gene analysis To analyses the differential expressed gene, six samples were send to do Microarray including three control samples and three treated samples. Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed with using the GeneSpring
GX v12.1 software package (Agilent Technologies). After quantile normalization of the raw data, mRNAs that at least 3 out of 6 samples have flags in Present or Marginal (``All Targets Value'') were chosen for further data analysis. The criterias of up-regulation and down-regulation of differential expressed genes were fold change >2 and fold change <0.5 respectively. Differential expressed mRNAs were identified through Fold Change filtering and the statistical significance of differential expressed mRNAs between the two groups were identified through random variance model Hierarchical Clustering and combined analysis were performed using homemade scripts. These p values were considered statistically significant if they were <0.05. 2.5 Validation of critical differential expressed gene The real-time Quantitative polymerase chain reaction (RT-qPCR) was used to verify the differential expression model profiles identified by gene Microarray. Because of high test fee, only some critical differential expressed genes were detected. The primers (Supplementary Table 1) of these genes were designed by the Primer-Blast (https://www.ncbi.nlm.nih.gov/tools/primer-blast). The relative quantification was performed using the 2−ΔΔCt by PCR Master Mix for SYBR Green assays (Vazyme, USA) on Real Time qPCR system (CFX-96, Bio-Rad Company, USA). Each gene per individual analyzed was performed in triplicate parallel dishes (n≥3 for RT-qPCR), and genes expression data was normalized to GAPDH. 2.6 Gene ontology analysis Gene ontology analysis was applied to analyze the biological process, cellular component and molecular function of the found differential expression genes according to the Gene ontology project (Ashburner et al., 2000). Fisher’s exact test was used to find if there were actually more overlaps than it would be expected by chance between the differential expression genes list and the GO annotation list. The p-value<0.05 denoted the significance of GO terms enrichment in the differential expression genes. The interaction net of these significant GOs was mapped to summarize the functional interactions of differential expression genes. 2.7 Pathway-net analysis Pathway analysis was applied to analyze the interaction net of the significant pathways of differential expression genes based on the KEGG database (http://www.kegg.jp/kegg/pathway.html) (Yi et al., 2006). KEGG analysis (KEGG data version: Release 70.1, June 1, 2014) was used for discovering the relation that was not easily visible from the changes of individual genes. Fisher's exact test was made to select the significant pathway and Fold change >2.0 and <0.5 were defined as up-regulation and down-regulation respectively for further analysis. The p-value <0.05 denotes the significance of the Pathway correlated to the conditions. The lower the p-value, the more significant is the Pathway. To summarize the pathway interaction of differential expression genes and find out the reason how certain pathway was activated, the interaction net of the
significant pathway of the differential expression genes was mapped to integrate the relationship pathway by outlining the interactions of related genes. 2.8 Gene-gene network analysis To build a gene–gene network, the interaction network was constructed in the STRING 10.0 (http://string-db.org/) according to the values among the differential expressed mRNAs and their interactions. STRING 10.0 is a resource to explore the known and predicted interactions of chemicals and protein-coding. To investigate the global network, the most important nodes were computationally identified by selecting up-expression and down-regulation of the differential expressed mRNAs. The parameters of required confidence (score) and interactors were set as medium confidence, no more than 10 interactors, respectively. p<0.05 was considered statistically significant and gene interactions could then be drawn based on the data. All functions encoded by these genes were found in gene database (http://www.ncbi.nlm.nih.gov/gene/).
3. Result 3.1 Cell viability rate and does As was shown in Fig. 1, the cell viability rate decreased significantly in a concentration dependent manner in all treatment doses after treating with Cr(VI) for 12, 24 and 48 h. The Student-Newman-Keuls( S-N-K ) test was used to find the difference of cell viability rate between control groups and treated groups. It was observed that with the time going and concentration rising, the Cr(VI) effects increased gradually. And when treated with 0.63 μM for 12 h, the experiment group 16HB cells began to show a significantly lower cell viability rate as compared with that in the control group Based on the IC50 value for Cr(VI), and the chromium concentration in workers’ blood from our previous occupational epidemiological investigation and findings (Hu et al., 2016; Li et al., 2015), the gene expression profile was performed at 10.00 μM Cr(VI) and the RT-qPCR at a variable treatment doses set to 0.00, 0.63, 1.23, 2.50, 5.00, and 10.00 μM. The treatment time was determined for 24 h. Note: The cell viability rate of 16HBE cells compared to controls following 12, 24 and 48 h treatment with different concentrations of Cr(VI) by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
GX v12.1 software package (Agilent Technologies). After quantile normalization of the raw data, mRNAs that at least 3 out of 6 samples have flags in Present or Marginal (``All Targets Value'') were chosen for further data analysis. The criterias of up-regulation and down-regulation of differential expressed genes were fold change >2 and fold change <0.5 respectively. Differential expressed mRNAs were identified through Fold Change filtering and the statistical significance of differential expressed mRNAs between the two groups were identified through random variance model Hierarchical Clustering and combined analysis were performed using homemade scripts. These p values were considered statistically significant if they were <0.05.
2.5 Validation of critical differential expressed gene The real-time Quantitative polymerase chain reaction (RT-qPCR) was used to verify the differential expression model profiles identified by gene Microarray. Because of high test fee, only some critical differential expressed genes were detected. The primers (Supplementary Table 1) of these genes were designed by the Primer-Blast (https://www.ncbi.nlm.nih.gov/tools/primer-blast). The relative quantification was performed using the 2−ΔΔCt by PCR Master Mix for SYBR Green assays (Vazyme, USA) on Real Time qPCR system (CFX-96, Bio-Rad Company, USA). Each gene per individual analyzed was performed in triplicate parallel dishes (n≥3 for RT-qPCR), and genes expression data was normalized to GAPDH. 2.6 Gene ontology analysis Gene ontology analysis was applied to analyze the biological process, cellular component and molecular function of the found differential expression genes according to the Gene ontology project (Ashburner et al., 2000). Fisher’s exact test was used to find if there were actually more overlaps than it would be expected by chance between the differential expression genes list and the GO annotation list. The p-value<0.05 denoted the significance of GO terms enrichment in the differential expression genes. The interaction net of these significant GOs was mapped to summarize the functional interactions of differential expression genes. 2.7 Pathway-net analysis Pathway analysis was applied to analyze the interaction net of the significant pathways of differential expression genes based on the KEGG database (http://www.kegg.jp/kegg/pathway.html) (Yi et al., 2006). KEGG analysis (KEGG data version: Release 70.1, June 1, 2014) was used for discovering the relation that was not easily visible from the changes of individual genes. Fisher's exact test was made to select the significant pathway and Fold change >2.0 and <0.5 were defined as up-regulation and down-regulation respectively for further analysis. The p-value <0.05 denotes the significance of the Pathway correlated to the conditions. The lower the p-value, the more significant is the Pathway. To summarize the pathway interaction of differential expression genes and find out the reason how certain pathway was activated, the interaction net of the
significant pathway of the differential expression genes was mapped to integrate the relationship pathway by outlining the interactions of related genes. 2.8 Gene-gene network analysis To build a gene–gene network, the interaction network was constructed in the STRING 10.0 (http://string-db.org/) according to the values among the differential expressed mRNAs and their interactions. STRING 10.0 is a resource to explore the known and predicted interactions of chemicals and protein-coding. To investigate the global network, the most important nodes were computationally identified by selecting up-expression and down-regulation of the differential expressed mRNAs. The parameters of required confidence (score) and interactors were set as medium confidence, no more than 10 interactors, respectively. p<0.05 was considered statistically significant and gene interactions could then be drawn based on the data. All functions encoded by these genes were found in gene database (http://www.ncbi.nlm.nih.gov/gene/).
3. Result 3.1 Cell viability rate and does As was shown in Fig. 1, the cell viability rate decreased significantly in a concentration dependent manner in all treatment doses after treating with Cr(VI) for 12, 24 and 48 h. The Student-Newman-Keuls( S-N-K ) test was used to find the difference of cell viability rate between control groups and treated groups. It was observed that with the time going and concentration rising, the Cr(VI) effects increased gradually. And when treated with 0.63 μM for 12 h, the experiment group 16HB cells began to show a significantly lower cell viability rate as compared with that in the control group Based on the IC50 value for Cr(VI), and the chromium concentration in workers’ blood from our previous occupational epidemiological investigation and findings (Hu et al., 2016; Li et al., 2015), the gene expression profile was performed at 10.00 μM Cr(VI) and the RT-qPCR at a variable treatment doses set to 0.00, 0.63, 1.23, 2.50, 5.00, and 10.00 μM. The treatment time was determined for 24 h. Note: The cell viability rate of 16HBE cells compared to controls following 12, 24 and 48 h treatment with different concentrations of Cr(VI) by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
2.7 Pathway-net analysis Pathway analysis was applied to analyze the interaction net of the significant pathways of differential expression genes based on the KEGG database (http://www.kegg.jp/kegg/pathway.html) (Yi et al., 2006). KEGG analysis (KEGG data version: Release 70.1, June 1, 2014) was used for discovering the relation that was not easily visible from the changes of individual genes. Fisher's exact test was made to select the significant pathway and Fold change >2.0 and <0.5 were defined as up-regulation and down-regulation respectively for further analysis. The p-value <0.05 denotes the significance of the Pathway correlated to the conditions. The lower the p-value, the more significant is the Pathway. To summarize the pathway interaction of differential expression genes and find out the reason how certain pathway was activated, the interaction net of the
significant pathway of the differential expression genes was mapped to integrate the relationship pathway by outlining the interactions of related genes. 2.8 Gene-gene network analysis To build a gene–gene network, the interaction network was constructed in the STRING 10.0 (http://string-db.org/) according to the values among the differential expressed mRNAs and their interactions. STRING 10.0 is a resource to explore the known and predicted interactions of chemicals and protein-coding. To investigate the global network, the most important nodes were computationally identified by selecting up-expression and down-regulation of the differential expressed mRNAs. The parameters of required confidence (score) and interactors were set as medium confidence, no more than 10 interactors, respectively. p<0.05 was considered statistically significant and gene interactions could then be drawn based on the data. All functions encoded by these genes were found in gene database (http://www.ncbi.nlm.nih.gov/gene/).
3. Result 3.1 Cell viability rate and does As was shown in Fig. 1, the cell viability rate decreased significantly in a concentration dependent manner in all treatment doses after treating with Cr(VI) for 12, 24 and 48 h. The Student-Newman-Keuls( S-N-K ) test was used to find the difference of cell viability rate between control groups and treated groups. It was observed that with the time going and concentration rising, the Cr(VI) effects increased gradually. And when treated with 0.63 μM for 12 h, the experiment group 16HB cells began to show a significantly lower cell viability rate as compared with that in the control group Based on the IC50 value for Cr(VI), and the chromium concentration in workers’ blood from our previous occupational epidemiological investigation and findings (Hu et al., 2016; Li et al., 2015), the gene expression profile was performed at 10.00 μM Cr(VI) and the RT-qPCR at a variable treatment doses set to 0.00, 0.63, 1.23, 2.50, 5.00, and 10.00 μM. The treatment time was determined for 24 h. Note: The cell viability rate of 16HBE cells compared to controls following 12, 24 and 48 h treatment with different concentrations of Cr(VI) by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
3. Result 3.1 Cell viability rate and does As was shown in Fig. 1, the cell viability rate decreased significantly in a concentration dependent manner in all treatment doses after treating with Cr(VI) for 12, 24 and 48 h. The Student-Newman-Keuls( S-N-K ) test was used to find the difference of cell viability rate between control groups and treated groups. It was observed that with the time going and concentration rising, the Cr(VI) effects increased gradually. And when treated with 0.63 μM for 12 h, the experiment group 16HB cells began to show a significantly lower cell viability rate as compared with that in the control group Based on the IC50 value for Cr(VI), and the chromium concentration in workers’ blood from our previous occupational epidemiological investigation and findings (Hu et al., 2016; Li et al., 2015), the gene expression profile was performed at 10.00 μM Cr(VI) and the RT-qPCR at a variable treatment doses set to 0.00, 0.63, 1.23, 2.50, 5.00, and 10.00 μM. The treatment time was determined for 24 h. Note: The cell viability rate of 16HBE cells compared to controls following 12, 24 and 48 h treatment with different concentrations of Cr(VI) by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
3.2 Effect of Cr(VI) on gene expression profile Comparative analysis of the overall Cr(VI) effects between 10μM Cr(VI) treated group and the control group revealed a significant change in the expression of 2273 genes (fold change >2 and <0.5 used for both up and down-regulation respectively; p <0.05) in 16HBE cells (Supplementary Fig 1). There were 938 genes significantly increased and 1335 decreased compared with the control group, in which the highest change increased more than 58.86 times.
3.3 Validation of the differential expression genes Note: Verification of the differential expression genes at different Cr(VI) treatment by S-N-K test. Results are mean ± standard deviation; a, Comparing with the control group, p<0.05; b, Comparing with the control group, p<0.001 3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
3.4 GO analysis of differential genes associated with Cr(VI) Cytotoxicity The comprehensive GO analysis of differentially expressed genes was used to gain deeper insight into the main functions associated with Cr(VI) cytotoxicity. It was found that a total of 2273 differential genes from cluster analysis were enriched to 878 GO terms. In this study, the gene was annotated to a specific node and then also considered to be annotated at the parent nodes. The significant terms with the lowest p value and their parents are shown in table 1. Through significant GO analysis of differential genes, the most prominent biological process involved in metabolic process, inflammatory response, positive regulation of cellular process, cell projection assembly, positive regulation of cellular metabolic process, cellular metabolic process, cell cycle and cell death. It was also found that differentially expressed genes were enriched in molecular functions like binding, phosphoprotein phosphatase activity, DNA binding, ion binding and so on. 3.5 Pathway analysis of the differential genes associated with Cr(VI) Cytotoxicity Based on the KEGG database, pathway analysis was conducted at DAVID 6.8 Beta (https://david.ncifcrf.gov/tools.jsp). In the current study, both up-regulation and down-regulation differentially expressed genes were selected to analyze the top ten significant enrichment pathways through the enrichment score value (-log10 (p value) ). It was suggested that the up-regulated differentially expressed genes were involved in many signaling pathways, such as p53 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway, osteoclast differentiation, cytokine-cytokine receptor interaction, legionellosis, hepatities B, FoxO signaling pathway, cell cycle and regulation of autophagy. The down-regulated biological functional pathways included endocytosis, hippo signaling pathway, dermatan sulfate, Wnt signaling pathway, basal cell carcinoma, tight junction, ubiquitin mediated proteolysis, alcoholism, non-homologous and osaminoglycan biosynthesis-heparan sulfate (Fig. 3). Note: a shows the pathway analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the pathway analysis of the up-regulation differential genes of 16HBE cells compared to control groups. 3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
3.6. Gene-net analysis of differential expressed genes related to Cr(VI) cytotoxicity The regulatory network maps were constructed to investigate the key genes involved in Cr(VI) cytotoxicity and their interaction. The potential direct interactions among those up-regulation and down-regulation genes were identified based on prior known protein-protein interactions and signaling pathways at STRING 10.0 between their up-regulation and down-regulation (Fig. 4). Among the differential expressed genes, EPB41, NHLRC1, HIST2H3D, HIST1H3G, RAD51B, PDS5B, HIST1H4I, SENP7,
RPA4, TP53BP1, XRCC4, CENP1, CCNF, TRDMT1, SMC2, PDE4D, RAD50 and TRADD were the most significantly decreased genes and had multiple connection nodes at the network center. These genes were mostly involved in p53 signaling pathway, MAPK signaling pathway, DNA repair and apoptosis. It was also found that there were lots of genes including CDC25A, PTK2B, CASP8, JUN, FOX, DUSP5, CCNT2, FBXL7, ZAK, CXCL8, TNFRSF10B, GADD4B and multiple inflammatory factors and cytokines located in the core of the gene network among the up-regulate genes. The functions of up-regulation genes are more or less involved in cellular proliferation and differentiation, oxidative stress, cell cycle and so on. Note: All differential genes interactions were analyzed by STRING 10.0. The differential genes were connected in a network based on prior known protein-protein interactions. Nodes represent genes. The area of nodes displays the degree based on the number of other genes that interact with this gene. Lines indicate interactions between genes. a shows the gene-gene network analysis of the down-regulation differential genes of 16HBE cells compared to control groups; b shows the gene-gene network analysis of the up-regulation differential genes of 16HBE cells compared to control groups.
4. Discussion As a well-recognized human carcinogen (1990), the strong oxidant Cr(VI) can produce multiple kinds of adverse health effects. The ultimate outcome of this process may due to an altered gene expression profile. However, the underlying molecular pathways or genes expression altered involving in the development of biological effects, tissue lesions or cancers still remain largely undetermined. In the current study, gene microarray and transcriptome analysis were performed to identify differential expressed genes, potential biomarkers of early Cr(VI) exposure and effect so as to elucidate mechanisms of Cr(VI) toxicity effects. Previous studies have found that there were considerable pathways or genes involved in Cr(VI)-induced cytotoxicity (Nigam et al., 2014). It is observed that some cellular pathways related with regulators of cell growth, proliferation, differentiation and apoptosis like MAPK pathways (Tessier and Pascal, 2006), Wnt/β-catenin signaling pathway (Wang et al., 2012), and activation of ERK (Extra cellular signal regulated kinase), JNK (C-Jun-N-terminal kinase), p38 (mitogen activated protein kinase) and so on have changed after Cr(VI) exposure (Chuang et al., 2000).Ye J and Shi X ( 2001) found that there were 220 significant dysregulation genes involved in the pathways of oxidative stress, Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, apoptosis, and carcinogenesis in human lung type II epithelial A549 cell when treated with 300 μM potassium dichromate for 2 h. What’ s more, Andrew and Warren (2003) observed that there were a cluster of 44 genes which encoded proteins related with the process of stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis modulated by a acute exposure (4 hours) to 10μM Cr(VI) in human bronchial epithelial BEAS-2B cells by using a limited microarray of 1200 genes. All of these suggest that Cr(VI) toxicity effects is a very
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
complicated process that involvesamount of gene expression changes and these altered genes could be involved in Ca2+ mobilization, energy metabolism, protein synthesis, cell cycle regulation, stress, apoptosis, anti-apoptotic, DNA repair and carcinogenesis .However, most of them focused on acute or high Cr(VI) exposure effects, and the size of the focused genes pool was a bit small. The gene expression profile for long term exposure to low-dose Cr(VI) still need to be conducted to elucidate biological response patterns, discover underlying mechanisms of toxicity, and identify the candidate Cr(VI)-specific genetic markers in response to Cr(VI) exposure. In this study, the treatment does and treated time were first determined according to the MTT assay and our previous occupational epidemiological studies results. Then, gene microarray analysis and bioinformatics analysis were performed to identify differential expressed genes and potential biomarkers of early Cr(VI) exposure. It was found that there were 2273 significant differential expressed genes after exposing to 10 μM Cr(VI) for 24 hours. A complex network has been formed among the altered gene profile. And some of genes expression alerted significantly in a concentration dependent manner to the Cr(VI) treatment concentrations. Our previous study (Li et al., 2014) has shown that there was a positive correlation between Cr(VI) concentration and DNA genetic damage. It indicated that some significantly differential expression genes would be worth to further research and might be used as potential early genetic damage biomarkers. Consistent with previous studies(Gavin et al., 2007; Nigam et al., 2014; Pabuwal et al., 2013; Ye and Shi, 2001), these responsive genes suggested that the toxicity effects of Cr(VI) exposure might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death and carcinogenesis in the cell. In the current study, a larger gene pool and a suitable Cr(VI) concentration were contribute to further elucidating potential mechanisms of toxicity, and identifying potential specific genetic markers of Cr(VI) exposure and effects. What’s more, as far as we all known, it was first found that the Cr(VI) toxicity effects might associate with the autophagy, endocytosis and DNA binding related genes. Additionally, we found that Toll-like receptor signaling pathway and FoxO signaling pathway were also bound up with the toxicity effects of Cr(VI) exposure for the first time. Gene expression profiles have provided an insight into early potential gene-based biomarkers and toxicity mechanism of Cr(VI) exposure. However, The molecular mechanism of the Cr(VI) toxicity effects was a very complicated regulation process. In addition to the gene expression changes, multiple factors including DNA methylation (Ali et al., 2011; Hu et al., 2016), the modulation of the non-coding RNA(Ali et al., 2011; Hu et al., 2016), the redox level (Myers, 2012) and genomic instability (Wise and Wise, 2012) have been shown to influence the Cr(VI) toxicity effects. As the complex effects of Cr(VI) exposure, these response genes may not play a direct or full role to the damage effects. So, to full elucidate Cr(VI) toxicity effects, it may need more intensive studies which focus on the validation of the potential biomarkers and whether the gene expression changes are affected through epigenetic processes or other factors in the future.
5. Conclusion In summary, our results provide a valuable target for understanding molecular mechanisms of the biological activities of Cr(VI) exposure. A total of 2273 significantly differential expressed genes formed a complex network and some gene expressions changed in a Cr(VI) concentration dependent manner: gene DUPS6, CXCL8, TNFRSF10B and GADD4B and Cr(VI) concentration of positive correlation, while gene EPB41 and NHLRC1 and Cr(VI) concentration of negative correlation. It shown that the Cr(VI) toxicity effects might involve in oxidative stress, inflammatory, energy metabolism, protein synthesis and metabolize, ion binding, cell morphogenesis, cell cycle regulation, cell death, carcinogenesis, autophagy, endocytosis and DNA binding by some specific pathway. Meanwhile, some alerted genes can be used as the potential early biomarker of Cr(VI) exposure. Conflict of interest The authors declare that there are no conflicts of interest.
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References [1990] Chromium, nickel and welding. IARC Monogr Eval Carcinog Risks Hum 49, 1-648. Ali, A.H., Kondo, K., Namura, T., Senba, Y., Takizawa, H., Nakagawa, Y., Toba, H., Kenzaki, K., Sakiyama, S., Tangoku, A.,;1; 2011. Aberrant DNA methylation of some tumor suppressor genes in lung cancers from workers with chromate exposure. Mol Carcinog 50, 89-99. Andrew, A.S., Warren, A.J., Barchowsky, A., Temple, K.A., Klei, L., Soucy, N.V., O'Hara, K.A., Hamilton, J.W.,;1; 2003. Genomic and proteomic profiling of responses to toxic metals in human lung cells. Environ Health Perspect 111, 825-835. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.,;1; 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-29. Beaver, L.M., Stemmy, E.J., Schwartz, A.M., Damsker, J.M., Constant, S.L., Ceryak, S.M., Patierno, S.R.,;1; 2009. Lung inflammation, injury, and proliferative response after repetitive particulate hexavalent chromium exposure. Environ Health Perspect 117, 1896-1902. Buttner, B., Beyersmann, D.,;1; 1985. Modification of the erythrocyte anion carrier by chromate. Xenobiotica 15, 735-741.
Chuang, S.M., Liou, G.Y., Yang, J.L.,;1; 2000. Activation of JNK, p38 and ERK mitogen-activated protein kinases by chromium(VI) is mediated through oxidative stress but does not affect cytotoxicity. Carcinogenesis 21, 1491-1500. Gao, Y., Xia, J.,;1; 2011. Chromium contamination accident in China: viewing environment policy of China. Environ Sci Technol 45, 8605-8606. Gavin, I.M., Gillis, B., Arbieva, Z., Prabhakar, B.S.,;1; 2007. Identification of human cell responses to hexavalent chromium. Environ Mol Mutagen 48, 650-657. Halasova, E., Matakova, T., Musak, L., Polakova, V., Letkova, L., Dobrota, D., Vodicka, P.,;1; 2012. Evaluating chromosomal damage in workers exposed to hexavalent chromium and the modulating role of polymorphisms of DNA repair genes. Int Arch Occup Environ Health 85, 473-481. Hu, G., Li, P., Li, Y., Wang, T., Gao, X., Zhang, W., Jia, G.,;1; 2016. Methylation levels of P16 and TP53 that are involved in DNA strand breakage of 16HBE cells treated by hexavalent chromium. Toxicol Lett 249, 15-21. Li, P., Gu, Y., Yu, S., Li, Y., Yang, J., Jia, G.,;1; 2014. Assessing the suitability of 8-OHdG and micronuclei as genotoxic biomarkers in chromate-exposed workers: a cross-sectional study. Bmj Open 4, e5979. Li, P., Li, Y., Zhang, J., Yu, S.F., Wang, Z.L., Jia, G.,;1; 2016. Establishment of a reference value for chromium in the blood for biological monitoring among occupational chromium workers. Toxicol Ind Health 32,1737-44. Li, Y., Hu, G., Li, P., Tang, S., Zhang, J., Jia, G.,;1;2016. miR-3940-5p enhances homologous recombination after DSB in Cr(VI) exposed 16HBE cell. Toxicology 344-346, 1-6. Mosmann, T.,;1; 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J Immunol Methods 65, 55-63. Myers, C.R.,;1; 2012. The effects of chromium(VI) on the thioredoxin system: implications for redox regulation. Free Radic Biol Med 52, 2091-2107. Nickens, K.P., Patierno, S.R., Ceryak, S.,;1; 2010. Chromium genotoxicity: A double-edged sword. Chem Biol Interact 188, 276-288. Nigam, A., Priya, S., Bajpai, P., Kumar, S.,;1; 2014. Cytogenomics of hexavalent chromium (Cr6+) exposed cells: A comprehensive review. Indian J Med Res 139, 349-370. Pabuwal, V., Boswell, M., Pasquali, A., Wise, S.S., Kumar, S., Shen, Y., Garcia, T., Lacerte, C., Wise, J.J., Wise, J.S., Warren, W., Walter, R.B.,;1; 2013. Transcriptomic analysis of cultured whale skin cells exposed to hexavalent chromium [Cr(VI)]. Aquat Toxicol 134-135, 74-81. Patlolla, A.K., Barnes, C., Hackett, D., Tchounwou, P.B.,;1; 2009. Potassium dichromate induced cytotoxicity, genotoxicity and oxidative stress in human liver carcinoma (HepG2) cells. Int J Environ Res Public Health 6, 643-653. Reynolds, M., Peterson, E., Quievryn, G., Zhitkovich, A.,;1; 2004. Human nucleotide excision repair efficiently removes chromium-DNA phosphate adducts and protects cells against chromate toxicity. J Biol Chem 279, 30419-30424. Rosenman, K.D., Stanbury, M.,;1; 1996. Risk of lung cancer among former chromium smelter workers. Am J Ind Med 29, 491-500. Tessier, D.M., Pascal, L.E.,;1; 2006. Activation of MAP kinases by hexavalent chromium, manganese and nickel in human lung epithelial cells. Toxicol Lett 167, 114-121.
Thompson, C.M., Kirman, C.R., Proctor, D.M., Haws, L.C., Suh, M., Hays, S.M., Hixon, J.G., Harris, M.A.,;1; 2014. A chronic oral reference dose for hexavalent chromium-induced intestinal cancer. J Appl Toxicol 34, 525-536. Wang, T., Jia, G., Zhang, J., Ma, Y., Feng, W., Liu, L., Zhang, N., Yan, L., Wang, X., Zhang, X., Liu, Z., Du X, Zhen, S.,;1; 2011. Renal impairment caused by chronic occupational chromate exposure. Int Arch Occup Environ Health 84, 393-401. Wang, X., Mandal, A.K., Saito, H., Pulliam, J.F., Lee, E.Y., Ke, Z.J., Lu, J., Ding, S., Li, L., Shelton, B.J., Tucker, T., Evers, B.M., Zhang, Z., Shi, X.,;1; 2012. Arsenic and chromium in drinking water promote tumorigenesis in a mouse colitis-associated colorectal cancer model and the potential mechanism is ROS-mediated Wnt/beta-catenin signaling pathway. Toxicol Appl Pharmacol 262, 11-21. Welling, R., Beaumont, J.J., Petersen, S.J., Alexeeff, G.V., Steinmaus, C.,;1; 2015. Chromium VI and stomach cancer: a meta-analysis of the current epidemiological evidence. Occup Environ Med 72, 151-159. Wise, S.S., Wise, J.S., 2012. Chromium and genomic stability. Mutat Res 733, 78-82. Xiao, F., Li, Y., Dai, L., Deng, Y., Zou, Y., Li, P., Yang, Y., Zhong, C.,;1; 2012. Hexavalent chromium targets mitochondrial respiratory chain complex I to induce reactive oxygen species-dependent caspase-3 activation in L-02 hepatocytes. Int J Mol Med 30, 629-635. Ye, J., Shi, X.,;1;2001. Gene expression profile in response to chromium-induced cell stress in A549 cells. Mol Cell Biochem 222, 189-197. Yi, M., Horton, J.D., Cohen, J.C., Hobbs, H.H., Stephens, R.M.,;1; 2006. WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data. Bmc Bioinformatics 7, 30. Zhitkovich, A., Peterson-Roth, E., Reynolds, M.,;1; 2005. Killing of chromium-damaged cells by mismatch repair and its relevance to carcinogenesis. Cell Cycle 4, 1050-1052.
Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database. Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding
TDENDOFDOCTD
count in gene set 651 657 536 475 244 140
p-value
52 325 577 224 444 558 92 1031 115 35
5.97e-05 8.26e-05 0.00012 0.000143 0.000143 0.000143 0.000154 0.000563 0.000657 0.002
72 288 630
0.00193 0.0204 0.0393
7.72e-06 1.4e-05 2.22e-05 2.22e-05 2.95e-05 5.93e-05
Acknowledgments This work was supported by National Natural Science Foundation of China (81573118, 81673118 and 81273043). References
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Figure 1. The effects of diferent treatment doses of Cr (VI) on the cell viability of 16HBE cells at 12, 24 and 48 h
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database.
The RNA integrity was well confirmed by standard denaturing agarose gel electrophoresis. Validation of the differential expression genes was done with RT-qPCR for several genes of interest, and expression was determined through comparison to GAPDH. The data were analyzed by S-N-K test to find the difference of expression between control goups and treated groups. It is found that there was a good agreement with the cDNA microarray analysis. As was revealed in Figure 2, there was positive correlations between Cr(VI) concentration and the DUPS6, CXCL8, TNFRSF10B and GADD4B gene expression, while EPB41 and NHLRC1 gene expressions were decreased in a concentration dependent manner. In additon, most of functions encoded by these genes were critical for cellular metabolic process, cell cycle and cell death based on the gene database.
Figure 2. Verification of the differential expression genes at different Cr(VI) treatment groups(x±SD)
Figure 3. Significant (top-ten) pathway analysis of differential expressed genes related to Cr(VI) exposure
Figure 4. Interaction gene-gene network analysis of differentially expressed mRNA related to Cr(VI) exposure. Table 1 Significant GO analysis of differential expressed genes related to Cr(VI) exposure Go term positive regulation of metabolic process regulation of metabolic process Biologica positive regulation of biological process l Process positive regulation of cellular process single-organism organelle organization anatomical structure formation involved in morphogenesis cell projection assembly positive regulation of cellular metabolic process regulation of cellular metabolic process intracellular signal transduction anatomical structure development regulation of primary metabolic process positive regulation of cell death Binding Molecula Cytoskeletal protein binding r phosphoprotein phosphatase activity Function Kinase binding DNA binding ion binding