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Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes

Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation,...

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Autores principales: Abele, Miriam, Doll, Etienne, Bayer, Florian P., Meng, Chen, Lomp, Nina, Neuhaus, Klaus, Scherer, Siegfried, Kuster, Bernhard, Ludwig, Christina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407251/
https://www.ncbi.nlm.nih.gov/pubmed/37391045
http://dx.doi.org/10.1016/j.mcpro.2023.100612
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author Abele, Miriam
Doll, Etienne
Bayer, Florian P.
Meng, Chen
Lomp, Nina
Neuhaus, Klaus
Scherer, Siegfried
Kuster, Bernhard
Ludwig, Christina
author_facet Abele, Miriam
Doll, Etienne
Bayer, Florian P.
Meng, Chen
Lomp, Nina
Neuhaus, Klaus
Scherer, Siegfried
Kuster, Bernhard
Ludwig, Christina
author_sort Abele, Miriam
collection PubMed
description Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in-solution digest. Peptides were separated on a 30-min linear microflow liquid chromatography gradient and analyzed in data-independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high-throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom.
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spelling pubmed-104072512023-08-09 Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes Abele, Miriam Doll, Etienne Bayer, Florian P. Meng, Chen Lomp, Nina Neuhaus, Klaus Scherer, Siegfried Kuster, Bernhard Ludwig, Christina Mol Cell Proteomics Research Bacteria are the most abundant and diverse organisms among the kingdoms of life. Due to this excessive variance, finding a unified, comprehensive, and safe workflow for quantitative bacterial proteomics is challenging. In this study, we have systematically evaluated and optimized sample preparation, mass spectrometric data acquisition, and data analysis strategies in bacterial proteomics. We investigated workflow performances on six representative species with highly different physiologic properties to mimic bacterial diversity. The best sample preparation strategy was a cell lysis protocol in 100% trifluoroacetic acid followed by an in-solution digest. Peptides were separated on a 30-min linear microflow liquid chromatography gradient and analyzed in data-independent acquisition mode. Data analysis was performed with DIA-NN using a predicted spectral library. Performance was evaluated according to the number of identified proteins, quantitative precision, throughput, costs, and biological safety. With this rapid workflow, over 40% of all encoded genes were detected per bacterial species. We demonstrated the general applicability of our workflow on a set of 23 taxonomically and physiologically diverse bacterial species. We could confidently identify over 45,000 proteins in the combined dataset, of which 30,000 have not been experimentally validated before. Our work thereby provides a valuable resource for the microbial scientific community. Finally, we grew Escherichia coli and Bacillus cereus in replicates under 12 different cultivation conditions to demonstrate the high-throughput suitability of the workflow. The proteomic workflow we present in this manuscript does not require any specialized equipment or commercial software and can be easily applied by other laboratories to support and accelerate the proteomic exploration of the bacterial kingdom. American Society for Biochemistry and Molecular Biology 2023-06-29 /pmc/articles/PMC10407251/ /pubmed/37391045 http://dx.doi.org/10.1016/j.mcpro.2023.100612 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research
Abele, Miriam
Doll, Etienne
Bayer, Florian P.
Meng, Chen
Lomp, Nina
Neuhaus, Klaus
Scherer, Siegfried
Kuster, Bernhard
Ludwig, Christina
Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes
title Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes
title_full Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes
title_fullStr Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes
title_full_unstemmed Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes
title_short Unified Workflow for the Rapid and In-Depth Characterization of Bacterial Proteomes
title_sort unified workflow for the rapid and in-depth characterization of bacterial proteomes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10407251/
https://www.ncbi.nlm.nih.gov/pubmed/37391045
http://dx.doi.org/10.1016/j.mcpro.2023.100612
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