Literature DB >> 31678905

Integration of metabolomics and transcriptomics reveals short-chain chlorinated paraffin-induced hepatotoxicity in male Sprague-Dawley rat.

Ningbo Geng1, Xiaoqian Ren2, Yufeng Gong1, Haijun Zhang3, Feidi Wang4, Liguo Xing5, Rong Cao1, Jiazhi Xu1, Yuan Gao1, John P Giesy6, Jiping Chen7.   

Abstract

BACKGROUND: Short-chain chlorinated paraffins (SCCPs) used in various industrial applications have been listed as new POPs. Previous studies based on high-dose exposures indicate their hepatotoxicity. However, their mechanisms of toxicity or adverse outcome pathways and health risks remain largely unknown.
OBJECTIVES: This study aimed to evaluate metabolic consequences of chronic dietary exposure to SCCPs at low doses and reveal the molecular mechanisms underlying hepatotoxicity of SCCPs.
METHODS: A combination of transcriptomics and metabolomics, together with general pathophysiological tests were performed to assess the hepatic response of male rats exposed to SCCPs.
RESULTS: Our results highlight two major modes of action: Inhibition of energy metabolism and activation of the peroxisome proliferator-activated receptor α (PPARα). Exposure to SCCPs suppressed oxidative phosphorylation, glycolysis, gluconeogenesis and turnover of ATP-ADP-AMP and thus results in deficiencies of amino acids and nucleotides in liver of the rat. Exposure to SCCPs affected expression levels of 13 genes downstream of PPARα that encode proteins associated with metabolism of fatty acids. As a result, peroxisomal and mitochondrial fatty acid β-oxidation, microsomal fatty acid ω-oxidation, and lipogenesis were accelerated.
CONCLUSIONS: Results of this work strongly support the conclusion that low-dose exposure to SCCPs can result in adverse outcomes in the rat model. Significant SCCP-induced inhibition of energy metabolism occurs at environmentally relevant dosages, which suggests that SCCPs exhibit metabolic toxicity. Interactions of SCCPs with PPARα signaling pathway can explain the disruption of lipids and amino acids metabolism.
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Energy metabolism; Metabolomic; PPARα; SCCPs; Transcriptomic

Mesh:

Substances:

Year:  2019        PMID: 31678905     DOI: 10.1016/j.envint.2019.105231

Source DB:  PubMed          Journal:  Environ Int        ISSN: 0160-4120            Impact factor:   9.621


  7 in total

Review 1.  Metabolomics as a valid analytical technique in environmental exposure research: application and progress.

Authors:  Shuang Wei; Yuanyun Wei; Yaqi Gong; Yonglin Chen; Jian Cui; Linwei Li; Hongxia Yan; Yueqiu Yu; Xiang Lin; Guoqing Li; Lan Yi
Journal:  Metabolomics       Date:  2022-05-31       Impact factor: 4.290

2.  Integrated metabolomics and transcriptomics reveal the anti-aging effect of melanin from Sepiella maindroni ink (MSMI) on D-galactose-induced aging mice.

Authors:  Yueyue Zhou; Weiwei Song; Chunlin Wang; Changkao Mu; Ronghua Li
Journal:  Aging (Albany NY)       Date:  2021-04-21       Impact factor: 5.682

3.  Kunxian Capsule for Rheumatoid Arthritis: Inhibition of Inflammatory Network and Reducing Adverse Reactions Through Drug Matching.

Authors:  Yujun Tang; Yi Zhang; Lin Li; Zhijun Xie; Chengping Wen; Lin Huang
Journal:  Front Pharmacol       Date:  2020-04-17       Impact factor: 5.810

Review 4.  Metabolomics: A New Approach in the Evaluation of Effects in Human Beings and Wildlife Associated with Environmental Exposition to POPs.

Authors:  Miriam Acosta-Tlapalamatl; Claudia Romo-Gómez; Arely Anaya-Hernández; Libertad Juárez-Santacruz; Juan Carlos Gaytán-Oyarzún; Otilio Arturo Acevedo-Sandoval; Edelmira García-Nieto
Journal:  Toxics       Date:  2022-07-09

Review 5.  Ecological and toxicological assessments of anthropogenic contaminants based on environmental metabolomics.

Authors:  Li-Juan Zhang; Lu Qian; Ling-Yun Ding; Lei Wang; Ming Hung Wong; Hu-Chun Tao
Journal:  Environ Sci Ecotechnol       Date:  2021-01-28

6.  Prediction Model of Aryl Hydrocarbon Receptor Activation by a Novel QSAR Approach, DeepSnap-Deep Learning.

Authors:  Yasunari Matsuzaka; Takuomi Hosaka; Anna Ogaito; Kouichi Yoshinari; Yoshihiro Uesawa
Journal:  Molecules       Date:  2020-03-13       Impact factor: 4.411

7.  Analysis by Metabolomics and Transcriptomics for the Energy Metabolism Disorder and the Aryl Hydrocarbon Receptor Activation in Male Reproduction of Mice and GC-2spd Cells Exposed to PM2.5.

Authors:  Fuquan Shi; Zhonghao Zhang; Jiankang Wang; Yimeng Wang; Jiuyang Deng; Yingfei Zeng; Peng Zou; Xi Ling; Fei Han; Jinyi Liu; Lin Ao; Jia Cao
Journal:  Front Endocrinol (Lausanne)       Date:  2022-01-03       Impact factor: 5.555

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.