2013Toxicological SciencesOpen access

Integrative Analysis of miRNA and Inflammatory Gene Expression After Acute Particulate Matter Exposure

Valeria Motta, Laura Angelici, Francesco Nordio, Valentina Bollati, Serena Fossati, Fabio Frascati, Valentina Tinaglia, Pier Alberto Bertazzi, Cristina Battaglia, Andrea Baccarelli

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Abstract

MicroRNAs (miRNAs) are environmentally sensitive inhibitors of gene expression that may mediate the effects of metal-rich particulate matter (PM) and toxic metals on human individuals. Previous environmental miRNA studies have investigated a limited number of candidate miRNAs and have not yet evaluated the functional effects on gene expression. In this study, we wanted to identify PM-sensitive miRNAs using microarray profiling on matched baseline and postexposure RNA from foundry workers with well-characterized exposure to metal-rich PM and to characterize miRNA relations with expression of candidate inflammatory genes. We applied microarray analysis of 847 human miRNAs and real-time PCR analysis of 18 candidate inflammatory genes on matched blood samples collected from foundry workers at baseline and after 3 days of work (postexposure). We identified differentially expressed miRNAs (fold change [FC] > 2 and p < 0.05) and correlated their expression with the inflammatory associated genes. We performed in silico network analysis in MetaCore v6.9 to characterize the biological pathways connecting miRNA-mRNA pairs. Microarray analysis identified four miRNAs that were differentially expressed in postexposure compared with baseline samples, including miR-421 (FC = 2.81, p < 0.001), miR-146a (FC = 2.62, p = 0.007), miR-29a (FC = 2.91, p < 0.001), and let-7g (FC = 2.73, p = 0.019). Using false discovery date adjustment for multiple comparisons, we found 11 miRNA-mRNA correlated pairs involving the 4 differentially expressed miRNAs and candidate inflammatory genes. In silico network analysis with MetaCore database identified biological interactions for all the 11 miRNA-mRNA pairs, which ranged from direct mRNA targeting to complex interactions with multiple intermediates. Acute PM exposure may affect gene regulation through PM-responsive miRNAs that directly or indirectly control inflammatory gene expression.

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MicroRNAs (miRNAs) are environmentally sensitive inhibitors of gene expression that may mediate the effects of metal-rich particulate matter (PM) and toxic metals on human individuals. Previous environmental miRNA studies have investigated a limited number of candidate miRNAs and have not yet evaluated the functional effects on gene expression. In this study, we wanted to identify PM-sensitive miRNAs using microarray profiling on matched baseline and postexposure RNA from foundry workers with well-characterized exposure to metal-rich PM and to characterize miRNA relations with expression of candidate inflammatory genes. We applied microarray analysis of 847 human miRNAs and real-time PCR analysis of 18 candidate inflammatory genes on matched blood samples collected from foundry workers at baseline and after 3 days of work (postexposure). We identified differentially expressed miRNAs (fold change [FC] > 2 and p < 0.05) and correlated their expression with the inflammatory associated genes. We performed in silico network analysis in MetaCore v6.9 to characterize the biological pathways connecting miRNA-mRNA pairs. Microarray analysis identified four miRNAs that were differentially expressed in postexposure compared with baseline samples, including miR-421 (FC = 2.81, p < 0.001), miR-146a (FC = 2.62, p = 0.007), miR-29a (FC = 2.91, p < 0.001), and let-7g (FC = 2.73, p = 0.019). Using false discovery date adjustment for multiple comparisons, we found 11 miRNA-mRNA correlated pairs involving the 4 differentially expressed miRNAs and candidate inflammatory genes. In silico network analysis with MetaCore database identified biological interactions for all the 11 miRNA-mRNA pairs, which ranged from direct mRNA targeting to complex interactions with multiple intermediates. Acute PM exposure may affect gene regulation through PM-responsive miRNAs that directly or indirectly control inflammatory gene expression.

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Available abstract

MicroRNAs (miRNAs) are environmentally sensitive inhibitors of gene expression that may mediate the effects of metal-rich particulate matter (PM) and toxic metals on human individuals. Previous environmental miRNA studies have investigated a limited number of candidate miRNAs and have not yet evaluated the functional effects on gene expression. In this study, we wanted to identify PM-sensitive miRNAs using microarray profiling on matched baseline and postexposure RNA from foundry workers with well-characterized exposure to metal-rich PM and to characterize miRNA relations with expression of candidate inflammatory genes. We applied microarray analysis of 847 human miRNAs and real-time PCR analysis of 18 candidate inflammatory genes on matched blood samples collected from foundry workers at baseline and after 3 days of work (postexposure). We identified differentially expressed miRNAs (fold change [FC] > 2 and p < 0.05) and correlated their expression with the inflammatory associated genes. We performed in silico network analysis in MetaCore v6.9 to characterize the biological pathways connecting miRNA-mRNA pairs. Microarray analysis identified four miRNAs that were differentially expressed in postexposure compared with baseline samples, including miR-421 (FC = 2.81, p < 0.001), miR-146a (FC = 2.62, p = 0.007), miR-29a (FC = 2.91, p < 0.001), and let-7g (FC = 2.73, p = 0.019). Using false discovery date adjustment for multiple comparisons, we found 11 miRNA-mRNA correlated pairs involving the 4 differentially expressed miRNAs and candidate inflammatory genes. In silico network analysis with MetaCore database identified biological interactions for all the 11 miRNA-mRNA pairs, which ranged from direct mRNA targeting to complex interactions with multiple intermediates. Acute PM exposure may affect gene regulation through PM-responsive miRNAs that directly or indirectly control inflammatory gene expression.

Key concepts: microRNA, In silico, Gene expression, Microarray, Gene expression profiling, Microarray analysis techniques, Fold change, DNA microarray

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