A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure
Background: Within the past two decades, high-profile cases of melamine (MA) exposure have raised significant toxicological concerns, particularly regarding food adulteration. While widely used as a fundamental organic chemical intermediate in various household products, MA's potential for unex...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | Ecotoxicology and Environmental Safety |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651325003653 |
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| author | Zhan Wang Zhaokai Zhou Zihao Zhao Junjie Zhang Shengli Zhang Luping Li Yingzhong Fan Qi Li |
| author_facet | Zhan Wang Zhaokai Zhou Zihao Zhao Junjie Zhang Shengli Zhang Luping Li Yingzhong Fan Qi Li |
| author_sort | Zhan Wang |
| collection | DOAJ |
| description | Background: Within the past two decades, high-profile cases of melamine (MA) exposure have raised significant toxicological concerns, particularly regarding food adulteration. While widely used as a fundamental organic chemical intermediate in various household products, MA's potential for unexpected toxicological synergy with its homolog, cyanuric acid (CA), remains a concern. This study aimed to investigate the nephrotoxicity of combined melamine and cyanuric acid (MC) exposure and its underlying mechanisms in rats through an integrative approach, combining network toxicology (NT), bioinformatics, and experimental validation. Materials and methods: Rats were exposed to MC at doses of 0/0 mg/kg/day (Control) and 63/63 mg/kg/day (MC) for four weeks. Kidney pathology, injury markers, and RNA sequencing (RNA-seq) data were analyzed to identify differentially expressed genes between the two groups. Bioinformatics analysis, including pathway enrichment and immune microenvironment analysis, was conducted to elucidate the underlying mechanisms of MC-induced kidney injury. Potential target proteins were identified using ChEMBL, STITCH, and GeneCards databases, and hub genes were screened using three machine learning algorithms: LASSO regression, Random Forest, and Molecular Complex Detection. Molecular docking simulations were performed to assess the interactions between MC and the identified hub genes. Results: MC exposure resulted in severe kidney morphological and histological changes, as well as elevated levels of kidney injury and fibrosis markers. RNA-seq analysis revealed significant enrichment of immuno-inflammatory and apoptosis-related pathways in the MC group. Immune microenvironment analysis confirmed the infiltration of pro-inflammatory immune cells. Network toxicology analysis identified 20 potential targets associated with MC-induced kidney injury. Two hub genes, Ren and Casp3, were identified as key regulators of the renin-angiotensin-aldosterone system (RAAS) activation and apoptosis, respectively. Further experimental validation, including Western blotting and immunofluorescence, confirmed the upregulation of these proteins. Molecular docking simulations demonstrated strong binding affinities between MC and the two hub proteins. Conclusion: MC exposure induces significant kidney injury and fibrosis. The activation of the RAAS pathway and apoptosis plays a crucial role in MC-mediated nephrotoxicity. However, additional vivo experimental validation is lacking. Future studies should focus on further exploration for the mechanism of MC-induced nephrotoxicity and more rigorous experimental validation. |
| format | Article |
| id | doaj-art-243eb42049b341e981ea6cb4606d1b9f |
| institution | OA Journals |
| issn | 0147-6513 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj-art-243eb42049b341e981ea6cb4606d1b9f2025-08-20T01:49:28ZengElsevierEcotoxicology and Environmental Safety0147-65132025-03-0129311802910.1016/j.ecoenv.2025.118029A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposureZhan Wang0Zhaokai Zhou1Zihao Zhao2Junjie Zhang3Shengli Zhang4Luping Li5Yingzhong Fan6Qi Li7Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Corresponding author.Background: Within the past two decades, high-profile cases of melamine (MA) exposure have raised significant toxicological concerns, particularly regarding food adulteration. While widely used as a fundamental organic chemical intermediate in various household products, MA's potential for unexpected toxicological synergy with its homolog, cyanuric acid (CA), remains a concern. This study aimed to investigate the nephrotoxicity of combined melamine and cyanuric acid (MC) exposure and its underlying mechanisms in rats through an integrative approach, combining network toxicology (NT), bioinformatics, and experimental validation. Materials and methods: Rats were exposed to MC at doses of 0/0 mg/kg/day (Control) and 63/63 mg/kg/day (MC) for four weeks. Kidney pathology, injury markers, and RNA sequencing (RNA-seq) data were analyzed to identify differentially expressed genes between the two groups. Bioinformatics analysis, including pathway enrichment and immune microenvironment analysis, was conducted to elucidate the underlying mechanisms of MC-induced kidney injury. Potential target proteins were identified using ChEMBL, STITCH, and GeneCards databases, and hub genes were screened using three machine learning algorithms: LASSO regression, Random Forest, and Molecular Complex Detection. Molecular docking simulations were performed to assess the interactions between MC and the identified hub genes. Results: MC exposure resulted in severe kidney morphological and histological changes, as well as elevated levels of kidney injury and fibrosis markers. RNA-seq analysis revealed significant enrichment of immuno-inflammatory and apoptosis-related pathways in the MC group. Immune microenvironment analysis confirmed the infiltration of pro-inflammatory immune cells. Network toxicology analysis identified 20 potential targets associated with MC-induced kidney injury. Two hub genes, Ren and Casp3, were identified as key regulators of the renin-angiotensin-aldosterone system (RAAS) activation and apoptosis, respectively. Further experimental validation, including Western blotting and immunofluorescence, confirmed the upregulation of these proteins. Molecular docking simulations demonstrated strong binding affinities between MC and the two hub proteins. Conclusion: MC exposure induces significant kidney injury and fibrosis. The activation of the RAAS pathway and apoptosis plays a crucial role in MC-mediated nephrotoxicity. However, additional vivo experimental validation is lacking. Future studies should focus on further exploration for the mechanism of MC-induced nephrotoxicity and more rigorous experimental validation.http://www.sciencedirect.com/science/article/pii/S0147651325003653MelamineCyanuric acidKidney injuryNetwork toxicologyBioinformaticsMachine learning |
| spellingShingle | Zhan Wang Zhaokai Zhou Zihao Zhao Junjie Zhang Shengli Zhang Luping Li Yingzhong Fan Qi Li A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure Ecotoxicology and Environmental Safety Melamine Cyanuric acid Kidney injury Network toxicology Bioinformatics Machine learning |
| title | A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure |
| title_full | A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure |
| title_fullStr | A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure |
| title_full_unstemmed | A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure |
| title_short | A network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co-exposure |
| title_sort | network toxicology and machine learning approach to investigate the mechanism of kidney injury from melamine and cyanuric acid co exposure |
| topic | Melamine Cyanuric acid Kidney injury Network toxicology Bioinformatics Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S0147651325003653 |
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