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A novel informatics concept for high-throughput shotgun lipidomics based on the molecular fragmentation query language.

Herzog R, Schwudke D, Schuhmann K, Sampaio JL, Bornstein SR, Schroeder M, Shevchenko A - Genome Biol. (2011)

Bottom Line: Shotgun lipidome profiling relies on direct mass spectrometric analysis of total lipid extracts from cells, tissues or organisms and is a powerful tool to elucidate the molecular composition of lipidomes.We present a novel informatics concept of the molecular fragmentation query language implemented within the LipidXplorer open source software kit that supports accurate quantification of individual species of any ionizable lipid class in shotgun spectra acquired on any mass spectrometry platform.

View Article: PubMed Central - HTML - PubMed

Affiliation: Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany.

ABSTRACT
Shotgun lipidome profiling relies on direct mass spectrometric analysis of total lipid extracts from cells, tissues or organisms and is a powerful tool to elucidate the molecular composition of lipidomes. We present a novel informatics concept of the molecular fragmentation query language implemented within the LipidXplorer open source software kit that supports accurate quantification of individual species of any ionizable lipid class in shotgun spectra acquired on any mass spectrometry platform.

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Related in: MedlinePlus

Architecture of LipidXplorer. Boxes represent functional modules and arrows represent data flow between the modules. The import module converts technical replicates (collections of MS and MS/MS spectra) into a flat file database termed the MasterScan (.sc). Then the interpretation module probes the MasterScan with interpretation queries written in molecular fragmentation query language (MFQL). Finally, the output module exports the findings in a user-defined format. All LipidXplorer settings (irrespective of what particular module they apply to) are controlled via a single graphical user interface.
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Figure 2: Architecture of LipidXplorer. Boxes represent functional modules and arrows represent data flow between the modules. The import module converts technical replicates (collections of MS and MS/MS spectra) into a flat file database termed the MasterScan (.sc). Then the interpretation module probes the MasterScan with interpretation queries written in molecular fragmentation query language (MFQL). Finally, the output module exports the findings in a user-defined format. All LipidXplorer settings (irrespective of what particular module they apply to) are controlled via a single graphical user interface.

Mentions: To this end, we propose a novel conceptual design that relies upon two-step data processing (Figure 2). First, a full pool of acquired MS and MS/MS spectra is organized into a single flat-file database termed as MasterScan. While building the MasterScan, the software recognizes related MS and MS/MS spectra and aligns them considering the peak attributes. Therefore, there is no need to interpret each spectrum individually, although important features of individual spectra are preserved. The second conceptually novel element is the molecular fragmentation query language, MFQL. We proposed that lipid identification should not rely on the comparison of experimental and reference spectra - whether the latter were produced in silico or in a separate experiment with reference substances. Instead, the known or assumed lipid fragmentation pathways can be formalized in a query, which subsequently probes the MasterScan. Spectra interpretation rules are not fixed and are not encoded into the software engine: at any time, users can define new rules or modify the existing rules and apply any number of interpretation rules in parallel.


A novel informatics concept for high-throughput shotgun lipidomics based on the molecular fragmentation query language.

Herzog R, Schwudke D, Schuhmann K, Sampaio JL, Bornstein SR, Schroeder M, Shevchenko A - Genome Biol. (2011)

Architecture of LipidXplorer. Boxes represent functional modules and arrows represent data flow between the modules. The import module converts technical replicates (collections of MS and MS/MS spectra) into a flat file database termed the MasterScan (.sc). Then the interpretation module probes the MasterScan with interpretation queries written in molecular fragmentation query language (MFQL). Finally, the output module exports the findings in a user-defined format. All LipidXplorer settings (irrespective of what particular module they apply to) are controlled via a single graphical user interface.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3091306&req=5

Figure 2: Architecture of LipidXplorer. Boxes represent functional modules and arrows represent data flow between the modules. The import module converts technical replicates (collections of MS and MS/MS spectra) into a flat file database termed the MasterScan (.sc). Then the interpretation module probes the MasterScan with interpretation queries written in molecular fragmentation query language (MFQL). Finally, the output module exports the findings in a user-defined format. All LipidXplorer settings (irrespective of what particular module they apply to) are controlled via a single graphical user interface.
Mentions: To this end, we propose a novel conceptual design that relies upon two-step data processing (Figure 2). First, a full pool of acquired MS and MS/MS spectra is organized into a single flat-file database termed as MasterScan. While building the MasterScan, the software recognizes related MS and MS/MS spectra and aligns them considering the peak attributes. Therefore, there is no need to interpret each spectrum individually, although important features of individual spectra are preserved. The second conceptually novel element is the molecular fragmentation query language, MFQL. We proposed that lipid identification should not rely on the comparison of experimental and reference spectra - whether the latter were produced in silico or in a separate experiment with reference substances. Instead, the known or assumed lipid fragmentation pathways can be formalized in a query, which subsequently probes the MasterScan. Spectra interpretation rules are not fixed and are not encoded into the software engine: at any time, users can define new rules or modify the existing rules and apply any number of interpretation rules in parallel.

Bottom Line: Shotgun lipidome profiling relies on direct mass spectrometric analysis of total lipid extracts from cells, tissues or organisms and is a powerful tool to elucidate the molecular composition of lipidomes.We present a novel informatics concept of the molecular fragmentation query language implemented within the LipidXplorer open source software kit that supports accurate quantification of individual species of any ionizable lipid class in shotgun spectra acquired on any mass spectrometry platform.

View Article: PubMed Central - HTML - PubMed

Affiliation: Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany.

ABSTRACT
Shotgun lipidome profiling relies on direct mass spectrometric analysis of total lipid extracts from cells, tissues or organisms and is a powerful tool to elucidate the molecular composition of lipidomes. We present a novel informatics concept of the molecular fragmentation query language implemented within the LipidXplorer open source software kit that supports accurate quantification of individual species of any ionizable lipid class in shotgun spectra acquired on any mass spectrometry platform.

Show MeSH
Related in: MedlinePlus