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Global gene expression changes in human embryonic lung fibroblasts induced by organic extracts from respirable air particles.

Líbalová H, Uhlířová K, Kléma J, Machala M, Šrám RJ, Ciganek M, Topinka J - Part Fibre Toxicol (2012)

Bottom Line: Dose-dependent increases in the number of significantly deregulated transcripts as well as dose-response relationships in the levels of individual transcripts were observed.The transcriptomic data did not differ substantially between the localities, suggesting that the air pollution originating mainly from various sources may have similar biological effects.Other important deregulated pathways in all 4 localities were ABC transporters (involved in the translocation of exogenous and endogenous metabolites across membranes and DNA repair), the Wnt and TGF-β signaling pathways (associated particularly with tumor promotion and progression), Steroid hormone biosynthesis (involved in the endocrine-disrupting activity of chemicals), and Glycerolipid metabolism (pathways involving the lipids with a glycerol backbone including lipid signaling molecules).

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Genetic Ecotoxicology, Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, 142 20 Prague 4, Czech Republic.

ABSTRACT

Background: Recently, we used cell-free assays to demonstrate the toxic effects of complex mixtures of organic extracts from urban air particles (PM2.5) collected in four localities of the Czech Republic (Ostrava-Bartovice, Ostrava-Poruba, Karvina and Trebon) which differed in the extent and sources of air pollution. To obtain further insight into the biological mechanisms of action of the extractable organic matter (EOM) from ambient air particles, human embryonic lung fibroblasts (HEL12469) were treated with the same four EOMs to assess changes in the genome-wide expression profiles compared to DMSO treated controls.

Method: For this purpose, HEL cells were incubated with subtoxic EOM concentrations of 10, 30, and 60 μg EOM/ml for 24 hours and global gene expression changes were analyzed using human whole genome microarrays (Illumina). The expression of selected genes was verified by quantitative real-time PCR.

Results: Dose-dependent increases in the number of significantly deregulated transcripts as well as dose-response relationships in the levels of individual transcripts were observed. The transcriptomic data did not differ substantially between the localities, suggesting that the air pollution originating mainly from various sources may have similar biological effects. This was further confirmed by the analysis of deregulated pathways and by identification of the most contributing gene modulations. The number of significantly deregulated KEGG pathways, as identified by Goeman's global test, varied, depending on the locality, between 12 to 29. The Metabolism of xenobiotics by cytochrome P450 exhibited the strongest upregulation in all 4 localities and CYP1B1 had a major contribution to the upregulation of this pathway. Other important deregulated pathways in all 4 localities were ABC transporters (involved in the translocation of exogenous and endogenous metabolites across membranes and DNA repair), the Wnt and TGF-β signaling pathways (associated particularly with tumor promotion and progression), Steroid hormone biosynthesis (involved in the endocrine-disrupting activity of chemicals), and Glycerolipid metabolism (pathways involving the lipids with a glycerol backbone including lipid signaling molecules).

Conclusion: The microarray data suggested a prominent role of activation of aryl hydrocarbon receptor-dependent gene expression.

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Related in: MedlinePlus

Correlation of the expression of selected transcripts from microarrays and quantitative real-time PCR analysis. The mean correlation across all the transcripts and localities was r = 0.91, (Pearson correlation coefficient).
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Figure 7: Correlation of the expression of selected transcripts from microarrays and quantitative real-time PCR analysis. The mean correlation across all the transcripts and localities was r = 0.91, (Pearson correlation coefficient).

Mentions: The gene expression of 11 selected significantly deregulated genes from microarray data in HEL cells was verified by qPCR. These genes include CYP1B1, MGST1, NKD2, BMP2, SMAD3, TBXAS1, CCND2, PTGS2, TJP1, WNT2, and ID2. The transcripts were selected to represent various deregulated pathways (Figure 4). Transcript levels of each selected gene were measured in each locality (Figure 6 A-D). In most cases, data proved dose-dependent up- or downregulation as indicated by Jonckheere-Terprsta monotonicity test. With the exception of the downregulation of SMAD3 gene involved in TGF-β and Wnt signaling pathways, all other transcripts verified by qPCR were closely correlated (Figure 7). The mean correlation across all the transcripts and localities was r = 0.91, the mean correlation without SMAD3 gene was r = 0.96 (r is the Pearson correlation coefficient).


Global gene expression changes in human embryonic lung fibroblasts induced by organic extracts from respirable air particles.

Líbalová H, Uhlířová K, Kléma J, Machala M, Šrám RJ, Ciganek M, Topinka J - Part Fibre Toxicol (2012)

Correlation of the expression of selected transcripts from microarrays and quantitative real-time PCR analysis. The mean correlation across all the transcripts and localities was r = 0.91, (Pearson correlation coefficient).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3275518&req=5

Figure 7: Correlation of the expression of selected transcripts from microarrays and quantitative real-time PCR analysis. The mean correlation across all the transcripts and localities was r = 0.91, (Pearson correlation coefficient).
Mentions: The gene expression of 11 selected significantly deregulated genes from microarray data in HEL cells was verified by qPCR. These genes include CYP1B1, MGST1, NKD2, BMP2, SMAD3, TBXAS1, CCND2, PTGS2, TJP1, WNT2, and ID2. The transcripts were selected to represent various deregulated pathways (Figure 4). Transcript levels of each selected gene were measured in each locality (Figure 6 A-D). In most cases, data proved dose-dependent up- or downregulation as indicated by Jonckheere-Terprsta monotonicity test. With the exception of the downregulation of SMAD3 gene involved in TGF-β and Wnt signaling pathways, all other transcripts verified by qPCR were closely correlated (Figure 7). The mean correlation across all the transcripts and localities was r = 0.91, the mean correlation without SMAD3 gene was r = 0.96 (r is the Pearson correlation coefficient).

Bottom Line: Dose-dependent increases in the number of significantly deregulated transcripts as well as dose-response relationships in the levels of individual transcripts were observed.The transcriptomic data did not differ substantially between the localities, suggesting that the air pollution originating mainly from various sources may have similar biological effects.Other important deregulated pathways in all 4 localities were ABC transporters (involved in the translocation of exogenous and endogenous metabolites across membranes and DNA repair), the Wnt and TGF-β signaling pathways (associated particularly with tumor promotion and progression), Steroid hormone biosynthesis (involved in the endocrine-disrupting activity of chemicals), and Glycerolipid metabolism (pathways involving the lipids with a glycerol backbone including lipid signaling molecules).

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Genetic Ecotoxicology, Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, 142 20 Prague 4, Czech Republic.

ABSTRACT

Background: Recently, we used cell-free assays to demonstrate the toxic effects of complex mixtures of organic extracts from urban air particles (PM2.5) collected in four localities of the Czech Republic (Ostrava-Bartovice, Ostrava-Poruba, Karvina and Trebon) which differed in the extent and sources of air pollution. To obtain further insight into the biological mechanisms of action of the extractable organic matter (EOM) from ambient air particles, human embryonic lung fibroblasts (HEL12469) were treated with the same four EOMs to assess changes in the genome-wide expression profiles compared to DMSO treated controls.

Method: For this purpose, HEL cells were incubated with subtoxic EOM concentrations of 10, 30, and 60 μg EOM/ml for 24 hours and global gene expression changes were analyzed using human whole genome microarrays (Illumina). The expression of selected genes was verified by quantitative real-time PCR.

Results: Dose-dependent increases in the number of significantly deregulated transcripts as well as dose-response relationships in the levels of individual transcripts were observed. The transcriptomic data did not differ substantially between the localities, suggesting that the air pollution originating mainly from various sources may have similar biological effects. This was further confirmed by the analysis of deregulated pathways and by identification of the most contributing gene modulations. The number of significantly deregulated KEGG pathways, as identified by Goeman's global test, varied, depending on the locality, between 12 to 29. The Metabolism of xenobiotics by cytochrome P450 exhibited the strongest upregulation in all 4 localities and CYP1B1 had a major contribution to the upregulation of this pathway. Other important deregulated pathways in all 4 localities were ABC transporters (involved in the translocation of exogenous and endogenous metabolites across membranes and DNA repair), the Wnt and TGF-β signaling pathways (associated particularly with tumor promotion and progression), Steroid hormone biosynthesis (involved in the endocrine-disrupting activity of chemicals), and Glycerolipid metabolism (pathways involving the lipids with a glycerol backbone including lipid signaling molecules).

Conclusion: The microarray data suggested a prominent role of activation of aryl hydrocarbon receptor-dependent gene expression.

Show MeSH
Related in: MedlinePlus