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An automated workflow for multi-omics screening of microbial model organisms
Multi-omics datasets are becoming of key importance to drive discovery in fundamental research as much as generating knowledge for applied biotechnology. However, the construction of such large datasets is usually time-consuming and expensive. Automation might enable to overcome these issues by stre...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199033/ https://www.ncbi.nlm.nih.gov/pubmed/37208327 http://dx.doi.org/10.1038/s41540-023-00277-6 |
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author | Donati, Stefano Mattanovich, Matthias Hjort, Pernille Jacobsen, Simo Abdessamad Baallal Blomquist, Sarah Dina Mangaard, Drude Gurdo, Nicolas Pastor, Felix Pacheco Maury, Jérôme Hanke, Rene Herrgård, Markus J. Wulff, Tune Jakočiūnas, Tadas Nielsen, Lars Keld McCloskey, Douglas |
author_facet | Donati, Stefano Mattanovich, Matthias Hjort, Pernille Jacobsen, Simo Abdessamad Baallal Blomquist, Sarah Dina Mangaard, Drude Gurdo, Nicolas Pastor, Felix Pacheco Maury, Jérôme Hanke, Rene Herrgård, Markus J. Wulff, Tune Jakočiūnas, Tadas Nielsen, Lars Keld McCloskey, Douglas |
author_sort | Donati, Stefano |
collection | PubMed |
description | Multi-omics datasets are becoming of key importance to drive discovery in fundamental research as much as generating knowledge for applied biotechnology. However, the construction of such large datasets is usually time-consuming and expensive. Automation might enable to overcome these issues by streamlining workflows from sample generation to data analysis. Here, we describe the construction of a complex workflow for the generation of high-throughput microbial multi-omics datasets. The workflow comprises a custom-built platform for automated cultivation and sampling of microbes, sample preparation protocols, analytical methods for sample analysis and automated scripts for raw data processing. We demonstrate possibilities and limitations of such workflow in generating data for three biotechnologically relevant model organisms, namely Escherichia coli, Saccharomyces cerevisiae, and Pseudomonas putida. |
format | Online Article Text |
id | pubmed-10199033 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101990332023-05-21 An automated workflow for multi-omics screening of microbial model organisms Donati, Stefano Mattanovich, Matthias Hjort, Pernille Jacobsen, Simo Abdessamad Baallal Blomquist, Sarah Dina Mangaard, Drude Gurdo, Nicolas Pastor, Felix Pacheco Maury, Jérôme Hanke, Rene Herrgård, Markus J. Wulff, Tune Jakočiūnas, Tadas Nielsen, Lars Keld McCloskey, Douglas NPJ Syst Biol Appl Article Multi-omics datasets are becoming of key importance to drive discovery in fundamental research as much as generating knowledge for applied biotechnology. However, the construction of such large datasets is usually time-consuming and expensive. Automation might enable to overcome these issues by streamlining workflows from sample generation to data analysis. Here, we describe the construction of a complex workflow for the generation of high-throughput microbial multi-omics datasets. The workflow comprises a custom-built platform for automated cultivation and sampling of microbes, sample preparation protocols, analytical methods for sample analysis and automated scripts for raw data processing. We demonstrate possibilities and limitations of such workflow in generating data for three biotechnologically relevant model organisms, namely Escherichia coli, Saccharomyces cerevisiae, and Pseudomonas putida. Nature Publishing Group UK 2023-05-19 /pmc/articles/PMC10199033/ /pubmed/37208327 http://dx.doi.org/10.1038/s41540-023-00277-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Donati, Stefano Mattanovich, Matthias Hjort, Pernille Jacobsen, Simo Abdessamad Baallal Blomquist, Sarah Dina Mangaard, Drude Gurdo, Nicolas Pastor, Felix Pacheco Maury, Jérôme Hanke, Rene Herrgård, Markus J. Wulff, Tune Jakočiūnas, Tadas Nielsen, Lars Keld McCloskey, Douglas An automated workflow for multi-omics screening of microbial model organisms |
title | An automated workflow for multi-omics screening of microbial model organisms |
title_full | An automated workflow for multi-omics screening of microbial model organisms |
title_fullStr | An automated workflow for multi-omics screening of microbial model organisms |
title_full_unstemmed | An automated workflow for multi-omics screening of microbial model organisms |
title_short | An automated workflow for multi-omics screening of microbial model organisms |
title_sort | automated workflow for multi-omics screening of microbial model organisms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199033/ https://www.ncbi.nlm.nih.gov/pubmed/37208327 http://dx.doi.org/10.1038/s41540-023-00277-6 |
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