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Sahoo AK, Chivukula N, Madgaonkar SR, Ramesh K, Marigoudar SR, Sharma KV, Samal A. Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives. Arch Toxicol 2024; 98:3299-3321. [PMID: 39097536 DOI: 10.1007/s00204-024-03825-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 07/24/2024] [Indexed: 08/05/2024]
Abstract
Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into ten priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, we showed the utility of the constructed plastic additives-AOP network by identifying highly relevant AOPs associated with benzo[a]pyrene (B[a]P), bisphenol A (BPA), and bis(2-ethylhexyl) phthalate (DEHP) and thereafter, explored the associated toxicity pathways in humans and aquatic species. Overall, the constructed plastic additives-AOP network will assist regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.
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Affiliation(s)
- Ajaya Kumar Sahoo
- Computational Biology Group, The Institute of Mathematical Sciences (IMSc), CIT Campus, Taramani, Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Nikhil Chivukula
- Computational Biology Group, The Institute of Mathematical Sciences (IMSc), CIT Campus, Taramani, Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Shreyes Rajan Madgaonkar
- Computational Biology Group, The Institute of Mathematical Sciences (IMSc), CIT Campus, Taramani, Chennai, 600113, India
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India
| | - Kundhanathan Ramesh
- Computational Biology Group, The Institute of Mathematical Sciences (IMSc), CIT Campus, Taramani, Chennai, 600113, India
| | | | - Krishna Venkatarama Sharma
- Ministry of Earth Sciences, National Centre for Coastal Research, Government of India, Pallikaranai, Chennai, 600100, India
| | - Areejit Samal
- Computational Biology Group, The Institute of Mathematical Sciences (IMSc), CIT Campus, Taramani, Chennai, 600113, India.
- Homi Bhabha National Institute (HBNI), Mumbai, 400094, India.
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Wyatt B, Davis AP, Wiegers TC, Wiegers J, Abrar S, Sciaky D, Barkalow F, Strong M, Mattingly CJ. Transforming environmental health datasets from the comparative toxicogenomics database into chord diagrams to visualize molecular mechanisms. FRONTIERS IN TOXICOLOGY 2024; 6:1437884. [PMID: 39104826 PMCID: PMC11298510 DOI: 10.3389/ftox.2024.1437884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 06/26/2024] [Indexed: 08/07/2024] Open
Abstract
In environmental health, the specific molecular mechanisms connecting a chemical exposure to an adverse endpoint are often unknown, reflecting knowledge gaps. At the public Comparative Toxicogenomics Database (CTD; https://ctdbase.org/), we integrate manually curated, literature-based interactions from CTD to compute four-unit blocks of information organized as a potential step-wise molecular mechanism, known as "CGPD-tetramers," wherein a chemical interacts with a gene product to trigger a phenotype which can be linked to a disease. These computationally derived datasets can be used to fill the gaps and offer testable mechanistic information. Users can generate CGPD-tetramers for any combination of chemical, gene, phenotype, and/or disease of interest at CTD; however, such queries typically result in the generation of thousands of CGPD-tetramers. Here, we describe a novel approach to transform these large datasets into user-friendly chord diagrams using R. This visualization process is straightforward, simple to implement, and accessible to inexperienced users that have never used R before. Combining CGPD-tetramers into a single chord diagram helps identify potential key chemicals, genes, phenotypes, and diseases. This visualization allows users to more readily analyze computational datasets that can fill the exposure knowledge gaps in the environmental health continuum.
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Affiliation(s)
- Brent Wyatt
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Allan Peter Davis
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Thomas C. Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Jolene Wiegers
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Sakib Abrar
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Daniela Sciaky
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Fern Barkalow
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Melissa Strong
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
| | - Carolyn J. Mattingly
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, United States
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Sahoo AK, Chivukula N, Ramesh K, Singha J, Marigoudar SR, Sharma KV, Samal A. An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 920:170968. [PMID: 38367714 DOI: 10.1016/j.scitotenv.2024.170968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/28/2024] [Accepted: 02/05/2024] [Indexed: 02/19/2024]
Abstract
Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium from five exposome-relevant databases using a data-centric approach, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs). By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.
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Affiliation(s)
- Ajaya Kumar Sahoo
- The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India
| | - Nikhil Chivukula
- The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India
| | | | - Jasmine Singha
- National Centre for Coastal Research, Ministry of Earth Sciences, Government of India, Pallikaranai, Chennai, India
| | | | - Krishna Venkatarama Sharma
- National Centre for Coastal Research, Ministry of Earth Sciences, Government of India, Pallikaranai, Chennai, India
| | - Areejit Samal
- The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India.
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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.
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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
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