1
|
Davis AP, Wiegers TC, Wiegers J, Wyatt B, Johnson RJ, Sciaky D, Barkalow F, Strong M, Planchart A, Mattingly CJ. CTD tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health. Toxicol Sci 2023; 195:155-168. [PMID: 37486259 PMCID: PMC10535784 DOI: 10.1093/toxsci/kfad069] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023] Open
Abstract
The molecular mechanisms connecting environmental exposures to adverse endpoints are often unknown, reflecting knowledge gaps. At the Comparative Toxicogenomics Database (CTD), we developed a bioinformatics approach that integrates manually curated, literature-based interactions from CTD to generate a "CGPD-tetramer": a 4-unit block of information organized as a step-wise molecular mechanism linking an initiating Chemical, an interacting Gene, a Phenotype, and a Disease outcome. Here, we describe a novel, user-friendly tool called CTD Tetramers that generates these evidence-based CGPD-tetramers for any curated chemical, gene, phenotype, or disease of interest. Tetramers offer potential solutions for the unknown underlying mechanisms and intermediary phenotypes connecting a chemical exposure to a disease. Additionally, multiple tetramers can be assembled to construct detailed modes-of-action for chemical-induced disease pathways. As well, tetramers can help inform environmental influences on adverse outcome pathways (AOPs). We demonstrate the tool's utility with relevant use cases for a variety of environmental chemicals (eg, perfluoroalkyl substances, bisphenol A), phenotypes (eg, apoptosis, spermatogenesis, inflammatory response), and diseases (eg, asthma, obesity, male infertility). Finally, we map AOP adverse outcome terms to corresponding CTD terms, allowing users to query for tetramers that can help augment AOP pathways with additional stressors, genes, and phenotypes, as well as formulate potential AOP disease networks (eg, liver cirrhosis and prostate cancer). This novel tool, as part of the complete suite of tools offered at CTD, provides users with computational datasets and their supporting evidence to potentially fill exposure knowledge gaps and develop testable hypotheses about environmental health.
Collapse
Affiliation(s)
- Allan Peter Davis
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Thomas C Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Jolene Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Brent Wyatt
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Robin J Johnson
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Daniela Sciaky
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Fern Barkalow
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Melissa Strong
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Antonio Planchart
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
- Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Carolyn J Mattingly
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
- Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina 27695, USA
| |
Collapse
|
2
|
Yang F, Wendusubilige, Kong J, Zong Y, Wang M, Jing C, Ma Z, Li W, Cao R, Jing S, Gao J, Li W, Wang J. Identifying oxidative stress-related biomarkers in idiopathic pulmonary fibrosis in the context of predictive, preventive, and personalized medicine using integrative omics approaches and machine-learning strategies. EPMA J 2023; 14:417-442. [PMID: 37605652 PMCID: PMC10439879 DOI: 10.1007/s13167-023-00334-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/09/2023] [Indexed: 08/23/2023]
Abstract
Background Idiopathic pulmonary fibrosis (IPF) is a rare interstitial lung disease with a poor prognosis that currently lacks effective treatment methods. Preventing the acute exacerbation of IPF, identifying the molecular subtypes of patients, providing personalized treatment, and developing individualized drugs are guidelines for predictive, preventive, and personalized medicine (PPPM / 3PM) to promote the development of IPF. Oxidative stress (OS) is an important pathological process of IPF. However, the relationship between the expression levels of oxidative stress-related genes (OSRGs) and clinical indices in patients with IPF is unclear; therefore, it is still a challenge to identify potential beneficiaries of antioxidant therapy. Because PPPM aims to recognize and manage diseases by integrating multiple methods, patient stratification and analysis based on OSRGs and identifying biomarkers can help achieve the above goals. Methods Transcriptome data from 250 IPF patients were divided into training and validation sets. Core OSRGs were identified in the training set and subsequently clustered to identify oxidative stress-related subtypes. The oxidative stress scores, clinical characteristics, and expression levels of senescence-associated secretory phenotypes (SASPs) of different subtypes were compared to identify patients who were sensitive to antioxidant therapy to conduct differential gene functional enrichment analysis and predict potential therapeutic drugs. Diagnostic markers between subtypes were obtained by integrating multiple machine learning methods, their expression levels were tested in rat models with different degrees of pulmonary fibrosis and validation sets, and nomogram models were constructed. CIBERSORT, single-cell RNA sequencing, and immunofluorescence staining were used to explore the effects of OSRGs on the immune microenvironment. Results Core OSRGs classified IPF into two subtypes. Patients classified into subtypes with low oxidative stress levels had better clinical scores, less severe fibrosis, and lower expression of SASP-related molecules. A reliable nomogram model based on five diagnostic markers was constructed, and these markers' expression stability was verified in animal experiments. The number of neutrophils in the immune microenvironment was significantly different between the two subtypes and was closely related to the degree of fibrosis. Conclusion Within the framework of PPPM, this work comprehensively explored the role of OSRGs and their mediated cellular senescence and immune processes in the progress of IPF and assessed their capabilities aspredictors of high oxidative stress and disease progression,targets of the vicious loop between regulated pulmonary fibrosis and OS for targeted secondary and tertiary prevention, andreferences for personalized antioxidant and antifibrotic therapies. Supplementary Information The online version contains supplementary material available at 10.1007/s13167-023-00334-4.
Collapse
Affiliation(s)
- Fan Yang
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of TCM Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Wendusubilige
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- Institute of Ethnic Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Jingwei Kong
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of TCM Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Yuhan Zong
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of TCM Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Manting Wang
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- National Institute of TCM Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Chuanqing Jing
- The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Zhaotian Ma
- College of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
- Institute of Ethnic Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Wanyang Li
- Department of Clinical Nutrition, Chinese Academy of Medical Sciences - Peking Union Medical College, Peking Union Medical College Hospital (Dongdan campus), Beijing, China
| | - Renshuang Cao
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Shuwen Jing
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Jie Gao
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Wenxin Li
- College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China
| | - Ji Wang
- National Institute of TCM Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China
| |
Collapse
|
3
|
Jeong J, Kim J, Choi J. Identification of molecular initiating events (MIE) using chemical database analysis and nuclear receptor activity assays for screening potential inhalation toxicants. Regul Toxicol Pharmacol 2023; 141:105391. [PMID: 37068727 DOI: 10.1016/j.yrtph.2023.105391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 03/13/2022] [Accepted: 04/13/2023] [Indexed: 04/19/2023]
Abstract
An adverse outcome pathway (AOP) framework can facilitate the use of alternative assays in chemical regulations by providing scientific evidence. Previously, an AOP, peroxisome proliferative-activating receptor gamma (PPARγ) antagonism that leads to pulmonary fibrosis, was developed. Based on a literature search, PPARγ inactivation has been proposed as a molecular initiating event (MIE). In addition, a list of candidate chemicals that could be used in the experimental validation was proposed using toxicity database and deep learning models. In this study, the screening of environmental chemicals for MIE was conducted using in silico and in vitro tests to maximize the applicability of this AOP for screening inhalation toxicants. Initially, potential inhalation exposure chemicals that are active in three or more key events were selected, and in silico molecular docking was performed. Among the chemicals with low binding energy to PPARγ, nine chemicals were selected for validation of the AOP using in vitro PPARγ activity assay. As a result, rotenone, triorthocresyl phosphate, and castor oil were proposed as PPARγ antagonists and stressor chemicals of the AOP. Overall, the proposed tiered approach of the database-in silico-in vitro can help identify the regulatory applicability and assist in the development and experimental validation of AOP.
Collapse
Affiliation(s)
- Jaeseong Jeong
- School of Environmental Engineering, University of Seoul, Dongdaemun-gu, Seoul, Republic of Korea
| | - Jiwan Kim
- School of Environmental Engineering, University of Seoul, Dongdaemun-gu, Seoul, Republic of Korea
| | - Jinhee Choi
- School of Environmental Engineering, University of Seoul, Dongdaemun-gu, Seoul, Republic of Korea.
| |
Collapse
|
4
|
Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly C. Comparative Toxicogenomics Database (CTD): update 2023. Nucleic Acids Res 2022; 51:D1257-D1262. [PMID: 36169237 PMCID: PMC9825590 DOI: 10.1093/nar/gkac833] [Citation(s) in RCA: 174] [Impact Index Per Article: 87.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/06/2022] [Accepted: 09/15/2022] [Indexed: 01/30/2023] Open
Abstract
The Comparative Toxicogenomics Database (CTD; http://ctdbase.org/) harmonizes cross-species heterogeneous data for chemical exposures and their biological repercussions by manually curating and interrelating chemical, gene, phenotype, anatomy, disease, taxa, and exposure content from the published literature. This curated information is integrated to generate inferences, providing potential molecular mediators to develop testable hypotheses and fill in knowledge gaps for environmental health. This dual nature, acting as both a knowledgebase and a discoverybase, makes CTD a unique resource for the scientific community. Here, we report a 20% increase in overall CTD content for 17 100 chemicals, 54 300 genes, 6100 phenotypes, 7270 diseases and 202 000 exposure statements. We also present CTD Tetramers, a novel tool that computationally generates four-unit information blocks connecting a chemical, gene, phenotype, and disease to construct potential molecular mechanistic pathways. Finally, we integrate terms for human biological media used in the CTD Exposure module to corresponding CTD Anatomy pages, allowing users to survey the chemical profiles for any tissue-of-interest and see how these environmental biomarkers are related to phenotypes for any anatomical site. These, and other webpage visual enhancements, continue to promote CTD as a practical, user-friendly, and innovative resource for finding information and generating testable hypotheses about environmental health.
Collapse
Affiliation(s)
- Allan Peter Davis
- To whom correspondence should be addressed. Tel: +1 919 515 5705; Fax: +1 919 515 3355;
| | - Thomas C Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Robin J Johnson
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Daniela Sciaky
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Jolene Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Carolyn J Mattingly
- Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695, USA,Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27695, USA
| |
Collapse
|
5
|
Li J, Wei W, Lai Z, Lai KP. In silico studies reveal the anti-osteosarcoma targets and action mechanisms of resveratrol. Process Biochem 2022. [DOI: 10.1016/j.procbio.2022.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|