Sample Preparation for Metabolite Analysis

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (30 November 2013) | Viewed by 45003

Special Issue Editor

MetaboConsult, Heanor, Derbyshire DE75 7UY, UK
Interests: metabolomics; metabonomics; metabolite-protein interactions; biological sample handling; NMR spectroscopy; chromatography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sample preparation is a critical, yet often undervalued stage of any metabolomics study. All too often, samples are pre-treated prior to analysis using approaches which have not been optimised, evaluated or validated.

However, previous publications within the area have demonstrated that judicious choice of sample preparation method is critical to analytical success. The choice of sample preparation method not only affects the resultant metabolomic profile of samples, but has even been demonstrated to affect the biochemical conclusions drawn from studies.

In this special issue, I therefore invite authors to share their best practice in the preparation of biological samples for metabolomics.

Dr. Clare A. Daykin
Guest Editor

Submission

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 300 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Keywords

  • sample preparation
  • deproteinisation
  • lipid extraction
  • cell extraction
  • tissue extraction
  • liquid-liquid extraction (LLE)
  • solid phase extraction (SPE)
  • protein precipitation
  • method development
  • off-line SPE
  • on-line SPE
  • metabolic profiles
  • metabolic patterns
  • biomarker detection
  • biomarker validation
  • personalized medicine
  • therapy optimization
  • metabolic modeling
  • metabolic network simulation
  • data integration
  • integrated databases

Published Papers (4 papers)

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Research

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Article
Xanthan Gum Removal for 1H-NMR Analysis of the Intracellular Metabolome of the Bacteria Xanthomonas axonopodis pv. citri 306
by Vanessa R. Pegos, Rafael R. Canevarolo, Aline P. Sampaio, Andrea Balan and Ana C. M. Zeri
Metabolites 2014, 4(2), 218-231; https://doi.org/10.3390/metabo4020218 - 22 Apr 2014
Cited by 33 | Viewed by 7691
Abstract
Xanthomonas is a genus of phytopathogenic bacteria, which produces a slimy, polysaccharide matrix known as xanthan gum, which involves, protects and helps the bacteria during host colonization. Although broadly used as a stabilizer and thickener in the cosmetic and food industries, xanthan gum [...] Read more.
Xanthomonas is a genus of phytopathogenic bacteria, which produces a slimy, polysaccharide matrix known as xanthan gum, which involves, protects and helps the bacteria during host colonization. Although broadly used as a stabilizer and thickener in the cosmetic and food industries, xanthan gum can be a troubling artifact in molecular investigations due to its rheological properties. In particular, a cross-reaction between reference compounds and the xanthan gum could compromise metabolic quantification by NMR spectroscopy. Aiming at an efficient gum extraction protocol, for a 1H-NMR-based metabolic profiling study of Xanthomonas, we tested four different interventions on the broadly used methanol-chloroform extraction protocol for the intracellular metabolic contents observation. Lower limits for bacterial pellet volumes for extraction were also probed, and a strategy is illustrated with an initial analysis of X. citri’s metabolism by 1H-NMR spectroscopy. Full article
(This article belongs to the Special Issue Sample Preparation for Metabolite Analysis)
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341 KiB  
Article
1H NMR Analysis of Cerebrospinal Fluid from Alzheimer’s Disease Patients: An Example of a Possible Misinterpretation Due to Non-Adjustment of pH
by Thomas Cruz, Stéphane Balayssac, Véronique Gilard, Robert Martino, Christian Vincent, Jérémie Pariente and Myriam Malet-Martino
Metabolites 2014, 4(1), 115-128; https://doi.org/10.3390/metabo4010115 - 19 Feb 2014
Cited by 8 | Viewed by 12242
Abstract
Two publications from the same research group reporting on the detection of new possible biomarkers for the early diagnosis of Alzheimer’s disease (AD), based on the analysis of cerebrospinal fluid samples (CSF) with 1H Nuclear Magnetic Resonance (NMR), are at the origin [...] Read more.
Two publications from the same research group reporting on the detection of new possible biomarkers for the early diagnosis of Alzheimer’s disease (AD), based on the analysis of cerebrospinal fluid samples (CSF) with 1H Nuclear Magnetic Resonance (NMR), are at the origin of the present study. The authors observed significant differences in 1H NMR spectra of CSF from AD patients and healthy controls and, thus, proposed some NMR signals (without attribution) as possible biomarkers. However, this work was carried out in non-standardized pH conditions. Our study aims at warning about a possible misinterpretation that can arise from 1H NMR analyses of CSF samples if pH adjustment is not done before NMR analysis. Indeed, CSF pH increases rapidly after removal and is subject to changes over conservation time. We first identify the NMR signals described by the authors as biomarkers. We then focus on the chemical shift variations of their NMR signals as a function of pH in both standard solutions and CSF samples. Finally, a principal component analysis of 1H NMR data demonstrates that the same CSF samples recorded at pH 8.1 and 10.0 are statistically differentiated. Full article
(This article belongs to the Special Issue Sample Preparation for Metabolite Analysis)
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Article
Evaluation of Extraction Protocols for Simultaneous Polar and Non-Polar Yeast Metabolite Analysis Using Multivariate Projection Methods
by Nicolas P. Tambellini, Vanina Zaremberg, Raymond J. Turner and Aalim M. Weljie
Metabolites 2013, 3(3), 592-605; https://doi.org/10.3390/metabo3030592 - 23 Jul 2013
Cited by 31 | Viewed by 10534
Abstract
Metabolomic and lipidomic approaches aim to measure metabolites or lipids in the cell. Metabolite extraction is a key step in obtaining useful and reliable data for successful metabolite studies. Significant efforts have been made to identify the optimal extraction protocol for various platforms [...] Read more.
Metabolomic and lipidomic approaches aim to measure metabolites or lipids in the cell. Metabolite extraction is a key step in obtaining useful and reliable data for successful metabolite studies. Significant efforts have been made to identify the optimal extraction protocol for various platforms and biological systems, for both polar and non-polar metabolites. Here we report an approach utilizing chemoinformatics for systematic comparison of protocols to extract both from a single sample of the model yeast organism Saccharomyces cerevisiae. Three chloroform/methanol/water partitioning based extraction protocols found in literature were evaluated for their effectiveness at reproducibly extracting both polar and non-polar metabolites. Fatty acid methyl esters and methoxyamine/trimethylsilyl derivatized aqueous compounds were analyzed by gas chromatography mass spectrometry to evaluate non-polar or polar metabolite analysis. The comparative breadth and amount of recovered metabolites was evaluated using multivariate projection methods. This approach identified an optimal protocol consisting of 64 identified polar metabolites from 105 ion hits and 12 fatty acids recovered, and will potentially attenuate the error and variation associated with combining metabolite profiles from different samples for untargeted analysis with both polar and non-polar analytes. It also confirmed the value of using multivariate projection methods to compare established extraction protocols. Full article
(This article belongs to the Special Issue Sample Preparation for Metabolite Analysis)
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Review
Microextraction by Packed Sorbent (MEPS) and Solid-Phase Microextraction (SPME) as Sample Preparation Procedures for the Metabolomic Profiling of Urine
by Catarina Silva, Carina Cavaco, Rosa Perestrelo, Jorge Pereira and José S. Câmara
Metabolites 2014, 4(1), 71-97; https://doi.org/10.3390/metabo4010071 - 27 Jan 2014
Cited by 68 | Viewed by 13708
Abstract
For a long time, sample preparation was unrecognized as a critical issue in the analytical methodology, thus limiting the performance that could be achieved. However, the improvement of microextraction techniques, particularly microextraction by packed sorbent (MEPS) and solid-phase microextraction (SPME), completely modified this [...] Read more.
For a long time, sample preparation was unrecognized as a critical issue in the analytical methodology, thus limiting the performance that could be achieved. However, the improvement of microextraction techniques, particularly microextraction by packed sorbent (MEPS) and solid-phase microextraction (SPME), completely modified this scenario by introducing unprecedented control over this process. Urine is a biological fluid that is very interesting for metabolomics studies, allowing human health and disease characterization in a minimally invasive form. In this manuscript, we will critically review the most relevant and promising works in this field, highlighting how the metabolomic profiling of urine can be an extremely valuable tool for the early diagnosis of highly prevalent diseases, such as cardiovascular, oncologic and neurodegenerative ones. Full article
(This article belongs to the Special Issue Sample Preparation for Metabolite Analysis)
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