Separating the wheat from the chaff: a prioritisation pipeline for the analysis of metabolomics datasets
Identifieur interne : 000A45 ( Main/Exploration ); précédent : 000A44; suivant : 000A46Separating the wheat from the chaff: a prioritisation pipeline for the analysis of metabolomics datasets
Auteurs : Andris Jankevics [Pays-Bas, Royaume-Uni] ; Maria Elena Merlo [Pays-Bas] ; Marcel De Vries [Pays-Bas] ; Roel J. Vonk [Pays-Bas] ; Eriko Takano [Pays-Bas] ; Rainer Breitling [Pays-Bas, Royaume-Uni]Source :
- Metabolomics [ 1573-3882 ] ; 2011.
Abstract
Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful and widely applied method for the study of biological systems, biomarker discovery and pharmacological interventions. LC-MS measurements are, however, significantly complicated by several technical challenges, including: (1) ionisation suppression/enhancement, disturbing the correct quantification of analytes, and (2) the detection of large amounts of separate derivative ions, increasing the complexity of the spectra, but not their information content. Here we introduce an experimental and analytical strategy that leads to robust metabolome profiles in the face of these challenges. Our method is based on rigorous filtering of the measured signals based on a series of sample dilutions. Such data sets have the additional characteristic that they allow a more robust assessment of detection signal quality for each metabolite. Using our method, almost 80% of the recorded signals can be discarded as uninformative, while important information is retained. As a consequence, we obtain a broader understanding of the information content of our analyses and a better assessment of the metabolites detected in the analyzed data sets. We illustrate the applicability of this method using standard mixtures, as well as cell extracts from bacterial samples. It is evident that this method can be applied in many types of LC-MS analyses and more specifically in untargeted metabolomics.
Url:
DOI: 10.1007/s11306-011-0341-0
PubMed: 22593722
PubMed Central: 3337394
Affiliations:
- Pays-Bas, Royaume-Uni
- Groningue (province), Écosse
- Glasgow, Groningue (ville)
- Université de Glasgow, Université de Groningue
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LC-MS measurements are, however, significantly complicated by several technical challenges, including: (1) ionisation suppression/enhancement, disturbing the correct quantification of analytes, and (2) the detection of large amounts of separate derivative ions, increasing the complexity of the spectra, but not their information content. Here we introduce an experimental and analytical strategy that leads to robust metabolome profiles in the face of these challenges. Our method is based on rigorous filtering of the measured signals based on a series of sample dilutions. Such data sets have the additional characteristic that they allow a more robust assessment of detection signal quality for each metabolite. Using our method, almost 80% of the recorded signals can be discarded as uninformative, while important information is retained. As a consequence, we obtain a broader understanding of the information content of our analyses and a better assessment of the metabolites detected in the analyzed data sets. We illustrate the applicability of this method using standard mixtures, as well as cell extracts from bacterial samples. It is evident that this method can be applied in many types of LC-MS analyses and more specifically in untargeted metabolomics.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Arita, M" uniqKey="Arita M">M Arita</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bentley, Sd" uniqKey="Bentley S">SD Bentley</name></author><author><name sortKey="Chater, Kf" uniqKey="Chater K">KF Chater</name></author><author><name sortKey="Cerde O Tarraga, Am" uniqKey="Cerde O Tarraga A">AM Cerdeño-Tárraga</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dettmer, K" uniqKey="Dettmer K">K Dettmer</name></author><author><name sortKey="Aronov, Pa" uniqKey="Aronov P">PA Aronov</name></author><author><name sortKey="Hammock, Bd" uniqKey="Hammock B">BD Hammock</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fiehn, O" uniqKey="Fiehn O">O 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sortKey="Smith, Ca" uniqKey="Smith C">CA Smith</name></author><author><name sortKey="O Aille, G" uniqKey="O Aille G">G O’Maille</name></author><author><name sortKey="Want, Ej" uniqKey="Want E">EJ Want</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Smith, Ca" uniqKey="Smith C">CA Smith</name></author><author><name sortKey="Want, Ej" uniqKey="Want E">EJ Want</name></author><author><name sortKey="O Aille, G" uniqKey="O Aille G">G O’Maille</name></author><author><name sortKey="Abagyan, R" uniqKey="Abagyan R">R Abagyan</name></author><author><name sortKey="Siuzdak, G" uniqKey="Siuzdak G">G Siuzdak</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Takano, E" uniqKey="Takano E">E Takano</name></author><author><name sortKey="Chakraburtty, R" uniqKey="Chakraburtty R">R Chakraburtty</name></author><author><name sortKey="Nihira, T" uniqKey="Nihira T">T Nihira</name></author><author><name sortKey="Yamada, Y" uniqKey="Yamada Y">Y Yamada</name></author><author><name sortKey="Bibb, Mj" uniqKey="Bibb M">MJ Bibb</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Tautenhahn, R" uniqKey="Tautenhahn R">R Tautenhahn</name></author><author><name sortKey="Bottcher, C" uniqKey="Bottcher C">C Böttcher</name></author><author><name sortKey="Neumann, S" uniqKey="Neumann S">S Neumann</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Windig, W" uniqKey="Windig W">W Windig</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zelena, E" uniqKey="Zelena E">E Zelena</name></author><author><name sortKey="Dunn, Wb" uniqKey="Dunn W">WB Dunn</name></author><author><name sortKey="Broadhurst, D" uniqKey="Broadhurst D">D Broadhurst</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Pays-Bas</li><li>Royaume-Uni</li></country><region><li>Groningue (province)</li><li>Écosse</li></region><settlement><li>Glasgow</li><li>Groningue (ville)</li></settlement><orgName><li>Université de Glasgow</li><li>Université de Groningue</li></orgName></list><tree><country name="Pays-Bas"><region name="Groningue (province)"><name sortKey="Jankevics, Andris" sort="Jankevics, Andris" uniqKey="Jankevics A" first="Andris" last="Jankevics">Andris Jankevics</name></region><name sortKey="Breitling, Rainer" sort="Breitling, Rainer" uniqKey="Breitling R" first="Rainer" last="Breitling">Rainer Breitling</name><name sortKey="De Vries, Marcel" sort="De Vries, Marcel" uniqKey="De Vries M" first="Marcel" last="De Vries">Marcel De Vries</name><name sortKey="Merlo, Maria Elena" sort="Merlo, Maria Elena" uniqKey="Merlo M" first="Maria Elena" last="Merlo">Maria Elena Merlo</name><name sortKey="Merlo, Maria Elena" sort="Merlo, Maria Elena" uniqKey="Merlo M" first="Maria Elena" last="Merlo">Maria Elena Merlo</name><name sortKey="Takano, Eriko" sort="Takano, Eriko" uniqKey="Takano E" first="Eriko" last="Takano">Eriko Takano</name><name sortKey="Vonk, Roel J" sort="Vonk, Roel J" uniqKey="Vonk R" first="Roel J." last="Vonk">Roel J. Vonk</name></country><country name="Royaume-Uni"><region name="Écosse"><name sortKey="Jankevics, Andris" sort="Jankevics, Andris" uniqKey="Jankevics A" first="Andris" last="Jankevics">Andris Jankevics</name></region><name sortKey="Breitling, Rainer" sort="Breitling, Rainer" uniqKey="Breitling R" first="Rainer" last="Breitling">Rainer Breitling</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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