Using Open Access Online Metabolomic Databases
Oliver Fiehn, PhD
Monday, June 24, 2019
Tweet
Transcript
Embed
Email
Bookmark
<<
<
>
>>
Tweet
Facebook
Email
Chapters
Introduction
Introduction of West Coast Metabolomics Center
Mass spectrometers are essential for data acquisition, but useless without software and databases
18 databases and tools hosted by WCMC
Primary metabolites must be derivatized for GC-MS
GC-TOF MS database BinBase catalogues deconvoluted mass spectra since 2005
GC-TOF MS BT vs Pegasus - Human plasma
GC-TOF MS BT vs Pegasus - Comparison of mass spectra
GC-TOF MS BT - Now with own BinBase database support
Example study on archaeology
What did North Californians smoke?
Native Americans are known to smoke or have smoked 55+ alkaloid plants
Study design after tribal interviews
Pipe soot keeps traces of intact metabolites
GC-TOF MS based plant metabolomics
GC-TOF MS based plant metabolomics also catalogues novel compounds in “Binbase”
What did North Californians smoke?
Fresh plant metabolomics clusters species with families
BinVestigate - The open access to BinBase @ UC Davis
BinVestigate on plants Arabidopsis thaliana: leaf, root, seed
BinVestigate on plants specific: Arabidopsis thaliana roots
BinVestigate on plants specific unknowns: Arabidopsis thaliana leaves
MS-DIAL uses MassBank of North America
MassBank of North America (MoNA) is an open-access mass spectral repository
MassBank of North America (MoNA) uses metadata
MassBank of North America (MoNA) upload auto-curation workflow
MassBank of North America
MassBank of North America (MoNA) database exchanges by SPLASH: a hashed MS identifier
MassBank of North America (MoNA) users 2017-2018
MassBank of North America (MoNA) integration with software, DBs
MassBank of North America (MoNA) downloads of complete libraries or by metadata
MassBank of North America (MoNA) downloads by structure classes (ClassyFire)
Data processing: MS-DIAL adducts – alignments – batch reporting
MS-DIAL 2.0 data processing w/ MS deconvolution GC-MS chromatograms: any vendor, any MS
Systematic error removal by random forest
InChI keys enable data sharing: Chemical Translation Service
MS-FINDER 2.0 for GC-MS spectra predictions - Examples: methylated epimetabolites
BinVestigate links with MS-DIAL, MS-Finder
BinVestigate gives relevance to unknowns
BinVestigate + MS-FINDER 2.0
Conclusions
Acknowledgments
No transcript for this webinar
More Info on LECO Sep Sci
Related Article
Request info