Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches
Untargeted metabolomics aims to provide a global picture of the metabolites present in the system under study. To this end, making a careful choice of sample preparation is mandatory to obtain reliable and reproducible biological information. In this study, eight different sample preparation techniq...
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doaj-47e64be30c054523b42e63eee48d9a362020-11-25T01:32:44ZengMDPI AGMetabolites2218-19892019-09-0191019310.3390/metabo9100193metabo9100193Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics ApproachesJulian Pezzatti0Matthieu Bergé1Julien Boccard2Santiago Codesido3Yoric Gagnebin4Patrick H. Viollier5Víctor González-Ruiz6Serge Rudaz7Institute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University Medical Centre, 1206 Geneva, SwitzerlandDepartment of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, University Medical Centre, 1206 Geneva, SwitzerlandInstitute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University Medical Centre, 1206 Geneva, SwitzerlandInstitute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University Medical Centre, 1206 Geneva, SwitzerlandInstitute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University Medical Centre, 1206 Geneva, SwitzerlandDepartment of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, University Medical Centre, 1206 Geneva, SwitzerlandInstitute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University Medical Centre, 1206 Geneva, SwitzerlandInstitute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University Medical Centre, 1206 Geneva, SwitzerlandUntargeted metabolomics aims to provide a global picture of the metabolites present in the system under study. To this end, making a careful choice of sample preparation is mandatory to obtain reliable and reproducible biological information. In this study, eight different sample preparation techniques were evaluated using <i>Caulobacter crescentus</i> as a model for Gram-negative bacteria. Two cell retrieval systems, two quenching and extraction solvents, and two cell disruption procedures were combined in a full factorial experimental design. To fully exploit the multivariate structure of the generated data, the ANOVA multiblock orthogonal partial least squares (AMOPLS) algorithm was employed to decompose the contribution of each factor studied and their potential interactions for a set of annotated metabolites. All main effects of the factors studied were found to have a significant contribution on the total observed variability. Cell retrieval, quenching and extraction solvent, and cell disrupting mechanism accounted respectively for 27.6%, 8.4%, and 7.0% of the total variability. The reproducibility and metabolome coverage of the sample preparation procedures were then compared and evaluated in terms of relative standard deviation (RSD) on the area for the detected metabolites. The protocol showing the best performance in terms of recovery, versatility, and variability was centrifugation for cell retrieval, using MeOH:H<sub>2</sub>O (8:2) as quenching and extraction solvent, and freeze-thaw cycles as the cell disrupting mechanism.https://www.mdpi.com/2218-1989/9/10/193metabolomicssample preparationhydrophilic interaction liquid chromatographyion mobility spectrometryhigh resolution mass spectrometrydesign of experimentsAMOPLS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Julian Pezzatti Matthieu Bergé Julien Boccard Santiago Codesido Yoric Gagnebin Patrick H. Viollier Víctor González-Ruiz Serge Rudaz |
spellingShingle |
Julian Pezzatti Matthieu Bergé Julien Boccard Santiago Codesido Yoric Gagnebin Patrick H. Viollier Víctor González-Ruiz Serge Rudaz Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches Metabolites metabolomics sample preparation hydrophilic interaction liquid chromatography ion mobility spectrometry high resolution mass spectrometry design of experiments AMOPLS |
author_facet |
Julian Pezzatti Matthieu Bergé Julien Boccard Santiago Codesido Yoric Gagnebin Patrick H. Viollier Víctor González-Ruiz Serge Rudaz |
author_sort |
Julian Pezzatti |
title |
Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches |
title_short |
Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches |
title_full |
Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches |
title_fullStr |
Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches |
title_full_unstemmed |
Choosing an Optimal Sample Preparation in <i>Caulobacter crescentus</i> for Untargeted Metabolomics Approaches |
title_sort |
choosing an optimal sample preparation in <i>caulobacter crescentus</i> for untargeted metabolomics approaches |
publisher |
MDPI AG |
series |
Metabolites |
issn |
2218-1989 |
publishDate |
2019-09-01 |
description |
Untargeted metabolomics aims to provide a global picture of the metabolites present in the system under study. To this end, making a careful choice of sample preparation is mandatory to obtain reliable and reproducible biological information. In this study, eight different sample preparation techniques were evaluated using <i>Caulobacter crescentus</i> as a model for Gram-negative bacteria. Two cell retrieval systems, two quenching and extraction solvents, and two cell disruption procedures were combined in a full factorial experimental design. To fully exploit the multivariate structure of the generated data, the ANOVA multiblock orthogonal partial least squares (AMOPLS) algorithm was employed to decompose the contribution of each factor studied and their potential interactions for a set of annotated metabolites. All main effects of the factors studied were found to have a significant contribution on the total observed variability. Cell retrieval, quenching and extraction solvent, and cell disrupting mechanism accounted respectively for 27.6%, 8.4%, and 7.0% of the total variability. The reproducibility and metabolome coverage of the sample preparation procedures were then compared and evaluated in terms of relative standard deviation (RSD) on the area for the detected metabolites. The protocol showing the best performance in terms of recovery, versatility, and variability was centrifugation for cell retrieval, using MeOH:H<sub>2</sub>O (8:2) as quenching and extraction solvent, and freeze-thaw cycles as the cell disrupting mechanism. |
topic |
metabolomics sample preparation hydrophilic interaction liquid chromatography ion mobility spectrometry high resolution mass spectrometry design of experiments AMOPLS |
url |
https://www.mdpi.com/2218-1989/9/10/193 |
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