45
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      2,3,7,8-Tetrachlorodibenzo- p-dioxin (TCDD)-elicited effects on bile acid homeostasis: Alterations in biosynthesis, enterohepatic circulation, and microbial metabolism

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          2,3,7,8-tetrachlorodibenzo- p-dioxin (TCDD) is a persistent environmental contaminant which elicits hepatotoxicity through activation of the aryl hydrocarbon receptor (AhR). Male C57BL/6 mice orally gavaged with TCDD (0.01–30 µg/kg) every 4 days for 28 days exhibited bile duct proliferation and pericholangitis. Mass spectrometry analysis detected a 4.6-fold increase in total hepatic bile acid levels, despite the coordinated repression of genes involved in cholesterol and primary bile acid biosynthesis including Cyp7a1. Specifically, TCDD elicited a >200-fold increase in taurolithocholic acid (TLCA), a potent G protein-coupled bile acid receptor 1 (GPBAR1) agonist associated with bile duct proliferation. Increased levels of microbial bile acid metabolism loci ( bsh, baiCD) are consistent with accumulation of TLCA and other secondary bile acids. Fecal bile acids decreased 2.8-fold, suggesting enhanced intestinal reabsorption due to induction of ileal transporters ( Slc10a2, Slc51a) and increases in whole gut transit time and intestinal permeability. Moreover, serum bile acids were increased 45.4-fold, consistent with blood-to-hepatocyte transporter repression ( Slco1a1, Slc10a1, Slco2b1, Slco1b2, Slco1a4) and hepatocyte-to-blood transporter induction ( Abcc4, Abcc3). These results suggest that systemic alterations in enterohepatic circulation, as well as host and microbiota bile acid metabolism, favor bile acid accumulation that contributes to AhR-mediated hepatotoxicity.

          Related collections

          Most cited references63

          • Record: found
          • Abstract: found
          • Article: not found

          Metabolomic analysis and visualization engine for LC-MS data.

          Metabolomic analysis by liquid chromatography-high-resolution mass spectrometry results in data sets with thousands of features arising from metabolites, fragments, isotopes, and adducts. Here we describe a software package, Metabolomic Analysis and Visualization ENgine (MAVEN), designed for efficient interactive analysis of LC-MS data, including in the presence of isotope labeling. The software contains tools for all aspects of the data analysis process, from feature extraction to pathway-based graphical data display. To facilitate data validation, a machine learning algorithm automatically assesses peak quality. Users interact with raw data primarily in the form of extracted ion chromatograms, which are displayed with overlaid circles indicating peak quality, and bar graphs of peak intensities for both unlabeled and isotope-labeled metabolite forms. Click-based navigation leads to additional information, such as raw data for specific isotopic forms or for metabolites changing significantly between conditions. Fast data processing algorithms result in nearly delay-free browsing. Drop-down menus provide tools for the overlay of data onto pathway maps. These tools enable animating series of pathway graphs, e.g., to show propagation of labeled forms through a metabolic network. MAVEN is released under an open source license at http://maven.princeton.edu.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Diet, microbiota, and microbial metabolites in colon cancer risk in rural Africans and African Americans.

            Epidemiologic studies have suggested that most cases of sporadic colon cancer can be attributed to diet. The recognition that colonic microbiota have a major influence on colonic health suggests that they might mediate colonic carcinogenesis. To examine the hypothesis that the influence of diet on colon cancer risk is mediated by the microbiota through their metabolites, we measured differences in colonic microbes and their metabolites in African Americans with a high risk and in rural native Africans with a low risk of colon cancer. Fresh fecal samples were collected from 12 healthy African Americans aged 50-65 y and from 12 age- and sex-matched native Africans. Microbiomes were analyzed with 16S ribosomal RNA gene pyrosequencing together with quantitative polymerase chain reaction of the major fermentative, butyrate-producing, and bile acid-deconjugating bacteria. Fecal short-chain fatty acids were measured by gas chromatography and bile acids by liquid chromatography-mass spectrometry. Microbial composition was fundamentally different, with a predominance of Prevotella in native Africans (enterotype 2) and of Bacteroides in African Americans (enterotype 1). Total bacteria and major butyrate-producing groups were significantly more abundant in fecal samples from native Africans. Microbial genes encoding for secondary bile acid production were more abundant in African Americans, whereas those encoding for methanogenesis and hydrogen sulfide production were higher in native Africans. Fecal secondary bile acid concentrations were higher in African Americans, whereas short-chain fatty acids were higher in native Africans. Our results support the hypothesis that colon cancer risk is influenced by the balance between microbial production of health-promoting metabolites such as butyrate and potentially carcinogenic metabolites such as secondary bile acids.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              FunGene: the functional gene pipeline and repository

              Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.
                Bookmark

                Author and article information

                Contributors
                tzachare@msu.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                19 July 2017
                19 July 2017
                2017
                : 7
                : 5921
                Affiliations
                [1 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Department of Biochemistry & Molecular Biology, , Michigan State University, ; East Lansing, MI 48824 USA
                [2 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Institute for Integrative Toxicology, , Michigan State University, ; East Lansing, MI 48824 USA
                [3 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Department of Chemistry, , Michigan State University, ; East Lansing, MI 48824 USA
                [4 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Department of Pathobiology & Diagnostic Investigation, , Michigan State University, ; East Lansing, MI 48824 USA
                Author information
                http://orcid.org/0000-0002-0839-3123
                Article
                5656
                10.1038/s41598-017-05656-8
                5517430
                28725001
                e6d4b848-2423-4bec-8c56-a2b28d6f838d
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 February 2017
                : 1 June 2017
                Categories
                Article
                Custom metadata
                © The Author(s) 2017

                Uncategorized
                Uncategorized

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content411

                Cited by24

                Most referenced authors1,026