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      Differential Response of Mono Mac 6, BEAS-2B, and Jurkat Cells to Indoor Dust

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          Abstract

          Background

          Airway toxicity of indoor dust is not sufficiently understood.

          Objectives

          Our goal in this study was to describe the effects of indoor dust on human monocyte, epithelial, and lymphocyte cell lines. We aimed to a) obtain a comprehensive and intelligible outline of the transcriptional response; b) correlate differential transcription with cellular protein secretion; c) identify cell line–specific features; and d) search for indoor dust–specific responses.

          Methods

          Settled dust was sampled in 42 German households, and various contaminants were characterized. We exposed Mono Mac 6, BEAS-2B, and Jurkat cells to 500 μg/mL indoor dust for 6 hr. Outcome parameters included the transcriptional profile of an oligonucleotide microarray covering 1,232 genes. Significantly enriched Gene Ontology themes were calculated. Supernatant protein levels of 24 inflammatory response proteins served to confirm transcriptional results.

          Results

          An intraclass correlation coefficient of 0.8 indicated reasonable microarray reproducibility. The transcriptional profile was characterized by enhancement of detoxification and a danger and defense response. Differential gene regulation correlated with protein secretion (Goodman and Kruskal’s gamma coefficient: 0.72; p < 0.01). Mono Mac 6 cells revealed the highest fraction of differentially expressed genes, dominated by up-regulation of various cytokines and chemokines. BEAS-2B cells revealed weaker changes in a limited set of inflammatory response proteins. No significant changes were observed in Jurkat cells.

          Conclusions

          Monocytes are particularly responsive to indoor dust. We observed a classical T-helper 1-dominated immune response, which suggested that bioorganic contaminants are relevant effectors in indoor dust.

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          Most cited references40

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          The Gene Ontology (GO) project in 2006

          (2005)
          The Gene Ontology (GO) project () develops and uses a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see ). The GO Consortium continues to improve to the vocabulary content, reflecting the impact of several novel mechanisms of incorporating community input. A growing number of model organism databases and genome annotation groups contribute annotation sets using GO terms to GO's public repository. Updates to the AmiGO browser have improved access to contributed genome annotations. As the GO project continues to grow, the use of the GO vocabularies is becoming more varied as well as more widespread. The GO project provides an ontological annotation system that enables biologists to infer knowledge from large amounts of data.
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            Evaluation of DNA microarray results with quantitative gene expression platforms.

            Roger D Canales, Yuling Luo, James C Willey … (2006)
            We have evaluated the performance characteristics of three quantitative gene expression technologies and correlated their expression measurements to those of five commercial microarray platforms, based on the MicroArray Quality Control (MAQC) data set. The limit of detection, assay range, precision, accuracy and fold-change correlations were assessed for 997 TaqMan Gene Expression Assays, 205 Standardized RT (Sta)RT-PCR assays and 244 QuantiGene assays. TaqMan is a registered trademark of Roche Molecular Systems, Inc. We observed high correlation between quantitative gene expression values and microarray platform results and found few discordant measurements among all platforms. The main cause of variability was differences in probe sequence and thus target location. A second source of variability was the limited and variable sensitivity of the different microarray platforms for detecting weakly expressed genes, which affected interplatform and intersite reproducibility of differentially expressed genes. From this analysis, we conclude that the MAQC microarray data set has been validated by alternative quantitative gene expression platforms thus supporting the use of microarray platforms for the quantitative characterization of gene expression.
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              GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies

              Bing Zhang, Denise Schmoyer, Stefan Kirov … (2004)
              Background Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets. Results We have created a web-based tool for data analysis and data visualization for sets of genes called GOTree Machine (GOTM). This tool was originally intended to analyze sets of co-regulated genes identified from microarray analysis but is adaptable for use with other gene sets from other high-throughput analyses. GOTree Machine generates a GOTree, a tree-like structure to navigate the Gene Ontology Directed Acyclic Graph for input gene sets. This system provides user friendly data navigation and visualization. Statistical analysis helps users to identify the most important Gene Ontology categories for the input gene sets and suggests biological areas that warrant further study. GOTree Machine is available online at . Conclusion GOTree Machine has a broad application in functional genomic, proteomic and other high-throughput methods that generate large sets of interesting genes; its primary purpose is to help users sort for interesting patterns in gene sets.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Environ Health Perspect
                Title: Environmental Health Perspectives
                Publisher: National Institute of Environmental Health Sciences
                ISSN (Print): 0091-6765
                Publication date (Print): September 2007
                Publication date (Electronic): 1 June 2007
                Volume: 115
                Issue: 9
                Pages: 1325-1332
                Affiliations
                [1 ] Department of Otorhinolaryngology, University Hospital Center, Ulm, Germany
                [2 ] Department of Environmental Health and Toxicology, State Agency for Nature and Environment of Schleswig Holstein, Kiel, Germany
                [3 ] Faculty of Chemistry, University of Oldenburg, Oldenburg, Germany
                Author notes
                Address correspondence to H. Riechelmann, Department of Otorhinolaryngology, University Hospital Center, Frauensteige 12, Ulm 89075, Germany. Telephone: 49 (0) 731/500 59504. Fax: 49 (0) 731/500 59506. E-mail: herbert.riechelmann@ 123456uniklinik-ulm.de

                The authors declare they have no competing financial interests.

                Article
                Publisher ID: ehp0115-001325
                DOI: 10.1289/ehp.9874
                PMC ID: 1964888
                PubMed ID: 17805423
                SO-VID: 332af414-b0d9-497b-8e79-c05cb23f3ae6
                Copyright © This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.
                History
                Date received : 1 November 2006
                Date accepted : 31 May 2007
                Categories
                Subject: Research

                ScienceOpen disciplines: Public health
                Keywords: chemistry,analytical,air pollution,expression profiling,cultured,cells,respiratory mucosa,indoor dust,immunoassay,gene
                Data availability:
                ScienceOpen disciplines: Public health
                Keywords: chemistry, analytical, air pollution, expression profiling, cultured, cells, respiratory mucosa, indoor dust, immunoassay, gene

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