A Transcriptomic Meta-analysis of Carbon Nanomaterials Toxicity on Lung Tissue
Апстракт
Nowadays, carbon nanomaterials (CNMs) are produced on an industrial scale and exposure to them can cause serious health issues. In this study, the long-term effects on the lung tissue transcriptome after administration of five CNMs: graphene oxide, reduced graphene oxide, small multi-walled carbon nanotubes (MWCNT), large MWCNT, and carbon black were examined. Since these CNMs differ physicochemically, the aim was to investigate whether these CNMs induced similar or different transcriptomic signatures. Publicly available transcriptomic datasets from the Gene Expression Omnibus database, under accession numbers GSE159707, GSE35284, and GSE55286 were used to extract treatment data. Two doses of CNMs were chosen, 0 μg/mouse in the control group and 18 μg/mouse in the treatment group. Transcriptomic profiling was performed four weeks after each treatment. The analysis of data was done using GEO2R tool, which employs Linear Models for Microarray Analysis (limma) R package to identify diffe...rentially expressed genes (DEGs) between the control group and each CNM-treated group. The DEGs were identified with a cut-off nominal p value of 0.05. Subsequently, a meta-analysis of the identified DEGs was performed using iPathwayGuide tool (Advaita Bio) to explore if the enriched signalling pathways or enriched diseases, are common for all five CNM treatments. The results have shown an enrichment of biological processes associated with immunological response in all CNMs treatments. Additionally, the research demonstrated that all CNMs treatments commonly induced Il-17 signalling pathway. Moreover, two disorders were identified as statistically significant: alpha-1-antitrypsin deficiency and chronic obstructive pulmonary disease. These findings are consistent with histopathological studies in mice. In conclusion, physicochemically distinct CNMs could have similar adverse biological effects. Furthermore, the findings have shown that a single CNM treatment could have long-term impacts. This suggest the potential of a targeted profiling of CNM exposed subjects to predict the detrimental outcome and timely employ prophylactic strategies.
Кључне речи:
carbon nanomaterials / lungs / transcriptome / bioinformaticsИзвор:
Belgrade Bioinformatics Conference, 2024Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200017 (Универзитет у Београду, Институт за нуклеарне науке Винча, Београд-Винча) (RS-MESTD-inst-2020-200017)
Напомена:
- BELBI - Belgrade Bioinformatics Conference; June 17-20th 2024, Belgrade.
- Wayback Machine link: https://belbi.bg.ac.rs/abstract/a-transcriptomic-meta-analysis-of-carbon-nanomaterials-toxicity-on-lung-tissue/
Колекције
Институција/група
VinčaTY - CONF AU - Seke, Mariana AU - Jovanović, Ivan G. AU - Mačak, Nataša AU - Živković, Maja AU - Stanković, Aleksandra PY - 2024 UR - https://vinar.vin.bg.ac.rs/handle/123456789/13445 AB - Nowadays, carbon nanomaterials (CNMs) are produced on an industrial scale and exposure to them can cause serious health issues. In this study, the long-term effects on the lung tissue transcriptome after administration of five CNMs: graphene oxide, reduced graphene oxide, small multi-walled carbon nanotubes (MWCNT), large MWCNT, and carbon black were examined. Since these CNMs differ physicochemically, the aim was to investigate whether these CNMs induced similar or different transcriptomic signatures. Publicly available transcriptomic datasets from the Gene Expression Omnibus database, under accession numbers GSE159707, GSE35284, and GSE55286 were used to extract treatment data. Two doses of CNMs were chosen, 0 μg/mouse in the control group and 18 μg/mouse in the treatment group. Transcriptomic profiling was performed four weeks after each treatment. The analysis of data was done using GEO2R tool, which employs Linear Models for Microarray Analysis (limma) R package to identify differentially expressed genes (DEGs) between the control group and each CNM-treated group. The DEGs were identified with a cut-off nominal p value of 0.05. Subsequently, a meta-analysis of the identified DEGs was performed using iPathwayGuide tool (Advaita Bio) to explore if the enriched signalling pathways or enriched diseases, are common for all five CNM treatments. The results have shown an enrichment of biological processes associated with immunological response in all CNMs treatments. Additionally, the research demonstrated that all CNMs treatments commonly induced Il-17 signalling pathway. Moreover, two disorders were identified as statistically significant: alpha-1-antitrypsin deficiency and chronic obstructive pulmonary disease. These findings are consistent with histopathological studies in mice. In conclusion, physicochemically distinct CNMs could have similar adverse biological effects. Furthermore, the findings have shown that a single CNM treatment could have long-term impacts. This suggest the potential of a targeted profiling of CNM exposed subjects to predict the detrimental outcome and timely employ prophylactic strategies. C3 - Belgrade Bioinformatics Conference T1 - A Transcriptomic Meta-analysis of Carbon Nanomaterials Toxicity on Lung Tissue UR - https://hdl.handle.net/21.15107/rcub_vinar_13445 ER -
@conference{ author = "Seke, Mariana and Jovanović, Ivan G. and Mačak, Nataša and Živković, Maja and Stanković, Aleksandra", year = "2024", abstract = "Nowadays, carbon nanomaterials (CNMs) are produced on an industrial scale and exposure to them can cause serious health issues. In this study, the long-term effects on the lung tissue transcriptome after administration of five CNMs: graphene oxide, reduced graphene oxide, small multi-walled carbon nanotubes (MWCNT), large MWCNT, and carbon black were examined. Since these CNMs differ physicochemically, the aim was to investigate whether these CNMs induced similar or different transcriptomic signatures. Publicly available transcriptomic datasets from the Gene Expression Omnibus database, under accession numbers GSE159707, GSE35284, and GSE55286 were used to extract treatment data. Two doses of CNMs were chosen, 0 μg/mouse in the control group and 18 μg/mouse in the treatment group. Transcriptomic profiling was performed four weeks after each treatment. The analysis of data was done using GEO2R tool, which employs Linear Models for Microarray Analysis (limma) R package to identify differentially expressed genes (DEGs) between the control group and each CNM-treated group. The DEGs were identified with a cut-off nominal p value of 0.05. Subsequently, a meta-analysis of the identified DEGs was performed using iPathwayGuide tool (Advaita Bio) to explore if the enriched signalling pathways or enriched diseases, are common for all five CNM treatments. The results have shown an enrichment of biological processes associated with immunological response in all CNMs treatments. Additionally, the research demonstrated that all CNMs treatments commonly induced Il-17 signalling pathway. Moreover, two disorders were identified as statistically significant: alpha-1-antitrypsin deficiency and chronic obstructive pulmonary disease. These findings are consistent with histopathological studies in mice. In conclusion, physicochemically distinct CNMs could have similar adverse biological effects. Furthermore, the findings have shown that a single CNM treatment could have long-term impacts. This suggest the potential of a targeted profiling of CNM exposed subjects to predict the detrimental outcome and timely employ prophylactic strategies.", journal = "Belgrade Bioinformatics Conference", title = "A Transcriptomic Meta-analysis of Carbon Nanomaterials Toxicity on Lung Tissue", url = "https://hdl.handle.net/21.15107/rcub_vinar_13445" }
Seke, M., Jovanović, I. G., Mačak, N., Živković, M.,& Stanković, A.. (2024). A Transcriptomic Meta-analysis of Carbon Nanomaterials Toxicity on Lung Tissue. in Belgrade Bioinformatics Conference. https://hdl.handle.net/21.15107/rcub_vinar_13445
Seke M, Jovanović IG, Mačak N, Živković M, Stanković A. A Transcriptomic Meta-analysis of Carbon Nanomaterials Toxicity on Lung Tissue. in Belgrade Bioinformatics Conference. 2024;. https://hdl.handle.net/21.15107/rcub_vinar_13445 .
Seke, Mariana, Jovanović, Ivan G., Mačak, Nataša, Živković, Maja, Stanković, Aleksandra, "A Transcriptomic Meta-analysis of Carbon Nanomaterials Toxicity on Lung Tissue" in Belgrade Bioinformatics Conference (2024), https://hdl.handle.net/21.15107/rcub_vinar_13445 .