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PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping
Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances’ mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptom...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024914/ https://www.ncbi.nlm.nih.gov/pubmed/36935498 http://dx.doi.org/10.1186/s13321-023-00710-2 |
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author | Bahl, Aileen Ibrahim, Celine Plate, Kristina Haase, Andrea Dengjel, Jörn Nymark, Penny Dumit, Verónica I. |
author_facet | Bahl, Aileen Ibrahim, Celine Plate, Kristina Haase, Andrea Dengjel, Jörn Nymark, Penny Dumit, Verónica I. |
author_sort | Bahl, Aileen |
collection | PubMed |
description | Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances’ mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13321-023-00710-2. |
format | Online Article Text |
id | pubmed-10024914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100249142023-03-21 PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping Bahl, Aileen Ibrahim, Celine Plate, Kristina Haase, Andrea Dengjel, Jörn Nymark, Penny Dumit, Verónica I. J Cheminform Research Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances’ mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13321-023-00710-2. Springer International Publishing 2023-03-19 /pmc/articles/PMC10024914/ /pubmed/36935498 http://dx.doi.org/10.1186/s13321-023-00710-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Bahl, Aileen Ibrahim, Celine Plate, Kristina Haase, Andrea Dengjel, Jörn Nymark, Penny Dumit, Verónica I. PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
title | PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
title_full | PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
title_fullStr | PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
title_full_unstemmed | PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
title_short | PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
title_sort | proteomas: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024914/ https://www.ncbi.nlm.nih.gov/pubmed/36935498 http://dx.doi.org/10.1186/s13321-023-00710-2 |
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