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- Publisher Website: 10.1021/ac2026578
- Scopus: eid_2-s2.0-84855396616
- PMID: 22111688
- WOS: WOS:000298763900067
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Article: MMSAT: Automated quantification of metabolites in selected reaction monitoring experiments
Title | MMSAT: Automated quantification of metabolites in selected reaction monitoring experiments |
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Authors | |
Issue Date | 2012 |
Citation | Analytical Chemistry, 2012, v. 84, n. 1, p. 470-474 How to Cite? |
Abstract | Selected reaction monitoring (SRM) is a mass spectrometry-based approach commonly used to increase analytical sensitivity and selectively for specific compounds in complex metabolomic samples. While the goal of well-designed SRM methods is to monitor for unique precursor-product ion pairs, in practice this is not always possible due to the diversity of the metabome and the resolution limits of mass spectrometers that are capable of SRM. Isobaric or near-isobaric precursor ions with different chromatographic properties but identical product ions often arise in complex samples. Without analytical standards, such metabolites will go undetected by conventional data analysis methods. Furthermore, a single SRM method may include simultaneous monitoring of tens to hundreds of different metabolites across multiple samples making quantification of all detected ions a challenging task. To facilitate the analysis of SRM data from complex metabolomic samples, we have developed the Metabolite Mass Spectrometry Analysis Tool (MMSAT). MMSAT is a web-based tool that objectively quantifies every metabolite peak detected in a set of samples and aligns peaks across multiple samples to enable quantitative comparison of each metabolite between samples. The analysis incorporates quantification of multiple peaks/ions that have different chromatographic retention times but are detected within a single SRM transition. We compare the performance of MMSAT against existing tools using a human glioblastoma tissue extract and illustrate its ability to automatically quantify multiple precursors within each of three different transitions. The Web-interface and source code is avaliable at http://www.cancerresearch.unsw.edu.au/crcweb.nsf/page/MMSAT. © 2011 American Chemical Society. |
Persistent Identifier | http://hdl.handle.net/10722/250982 |
ISSN | 2023 Impact Factor: 6.7 2023 SCImago Journal Rankings: 1.621 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wong, Jason W H | - |
dc.contributor.author | Abuhusain, Hazem J. | - |
dc.contributor.author | McDonald, Kerrie L. | - |
dc.contributor.author | Don, Anthony S. | - |
dc.date.accessioned | 2018-02-01T01:54:15Z | - |
dc.date.available | 2018-02-01T01:54:15Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Analytical Chemistry, 2012, v. 84, n. 1, p. 470-474 | - |
dc.identifier.issn | 0003-2700 | - |
dc.identifier.uri | http://hdl.handle.net/10722/250982 | - |
dc.description.abstract | Selected reaction monitoring (SRM) is a mass spectrometry-based approach commonly used to increase analytical sensitivity and selectively for specific compounds in complex metabolomic samples. While the goal of well-designed SRM methods is to monitor for unique precursor-product ion pairs, in practice this is not always possible due to the diversity of the metabome and the resolution limits of mass spectrometers that are capable of SRM. Isobaric or near-isobaric precursor ions with different chromatographic properties but identical product ions often arise in complex samples. Without analytical standards, such metabolites will go undetected by conventional data analysis methods. Furthermore, a single SRM method may include simultaneous monitoring of tens to hundreds of different metabolites across multiple samples making quantification of all detected ions a challenging task. To facilitate the analysis of SRM data from complex metabolomic samples, we have developed the Metabolite Mass Spectrometry Analysis Tool (MMSAT). MMSAT is a web-based tool that objectively quantifies every metabolite peak detected in a set of samples and aligns peaks across multiple samples to enable quantitative comparison of each metabolite between samples. The analysis incorporates quantification of multiple peaks/ions that have different chromatographic retention times but are detected within a single SRM transition. We compare the performance of MMSAT against existing tools using a human glioblastoma tissue extract and illustrate its ability to automatically quantify multiple precursors within each of three different transitions. The Web-interface and source code is avaliable at http://www.cancerresearch.unsw.edu.au/crcweb.nsf/page/MMSAT. © 2011 American Chemical Society. | - |
dc.language | eng | - |
dc.relation.ispartof | Analytical Chemistry | - |
dc.title | MMSAT: Automated quantification of metabolites in selected reaction monitoring experiments | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1021/ac2026578 | - |
dc.identifier.pmid | 22111688 | - |
dc.identifier.scopus | eid_2-s2.0-84855396616 | - |
dc.identifier.volume | 84 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 470 | - |
dc.identifier.epage | 474 | - |
dc.identifier.isi | WOS:000298763900067 | - |
dc.identifier.issnl | 0003-2700 | - |