Second Annual Meeting of COST Action CA17111 INTEGRAPE 2020 Ljubljana, Slovenia

1. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
Panagiotis Arapitsas
panagiotis.arapitsas@fmach.it
https://sites.google.com/a/fmach.it/wine-metabolomics/
Second Annual Meeting of COST Action CA17111 "INTEGRAPE 2020
Ljubljana

2. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
2000
Metabolomics
metabolomics is the comprehensive and holistic study of the metabolome
the complete set of small-molecule metabolites to be
found within a biological sample

3. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
2000
Metabolomics
Vitis + metabolomics
(145)
grape + metabolomics
(224)
wine + metabolomics
(263)
metabolomics
(39 541)
Metabolomics publications in Vitis, grape and wine represent the 0,5% of the publication in Metabolomics
www.scopus.com

4. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
2007
Proposed
 minimum reporting standards for sample collection and preparation
 minimum reporting standards relative to chromatography
 minimum reporting standards relative to mass spectrometry and NMR
 minimum reporting standards relative to instrumental performance and method
validation
 minimum reporting standards relative to data preprocessing
 minimum reporting standards relative to metabolite identification
Standards
2000

5. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
FEM
2008 (2010)2000 2007

6. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
EMBO
Ontologies
Public repositories
Standardization
ID
20082000 20132007

7. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
FAIR
Findable
Accessible
Interoperable
Reusable
20082000 2013 20162007

8. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
Data
measurements
raw files
transformed data
Mass spectrometry
NMR
DAD
Targeted analysis
Untargeted analysis
FAIR
20082000 2013 20162007

9. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
 Holistic approach: complementary platforms
 Multidisciplinary: chemistry + biology + physics + mathematics + informatics
 Untargeted: the metabolites are by definition not pre-defined
 Unfeasible validation: hundreds to thousands metabolites, many unknown
 Self-awareness: minimum reporting standard / levels of annotation
Mass Spectrometry (MS)
Direct infusion/Imaging
Gas Chromatography (GC)
Liquid Chromatography (LC)
Capillary Electrophoresis (EC)
Nuclear Magnetic Resonance (NMR) NMR: up to 100 metabolites
few hundreds metabolites
ESI-
ESI+
Reverse Phase (RP)
Normal Phase (NP)
few hundreds metabolites
few thousands metabolites
GCxGC
few hundreds metabolites
Derivatisation

10. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
Prefer targeted methods when:
 You focus in a targeted group or single metabolite (you know what to measure)
 You want/need the absolute concentration (except NMR)
 You don’t know very good your instrument (analytical chemistry skills)
 You are not familiar with compound annotation
 You have a poor knowledge of your sample metabolome
 You don’t have plenty of time for data analysis / you want fast results
 You want to work alone (biology, organic chemistry, biochemistry, analytical chemistry,
bioinformatics, chemo-metrics)

11. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
is data about datametaData
Prime name: Muscat Alexandria
Color: Blanc
VIVC ID: 8241
Vintage: 2019
Harvest day: 1 September 2019
Collection: FEM
FAIR
20102000 2013 20162007

12. FAIR
20082000 2013 20162007
Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
is data about datametaData
Prime name: Muscat Alexandria
Color: Blanc
VIVC ID: 8241
Vintage: 2019
Harvest day: 1 September 2019
Collection: FEM

13. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
is data about datametaData
Malvidin 3-O-glucoside
Malvidin 3-glucoside
Malvidin glucoside
Oenin
Enin
Enoside
Ligulin
Malvidin 3-O-beta-D-glucopyranoside
Malvidin 3-O-b-D-glucoside
Malvidin 3-O-β-D-glucoside
O
+
OH
OH
O
OH
O
OO
OH
OH
OH
OH
HMDB: HMDB0030777
Phenol explorer: 36
FoodDB: FDB00214
KNApSAcK: C00006735
Chemspider: 391785
Pubchem: 443652
ChEBI: 31799
ACToR: 18470-06-9
Brenda: 23247, 44396, 17666, 60579
ChEBI: 31799
KEGG: C12140
Metabolights: MTBLC31799
Use at least one
FAIR
20082000 2013 20162007

14. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
Sample Collection (biological replicates, method)
Sample Storage (period, temperature, atmosphere)
Sample Processing (lyophilization, homogenization)
Sample Relocation/Shipping
Sample Preparation
(Solvents, pH, temperature, time, volumes, weights, concentration, clean up, dilutions,
Resolubilization, degassing, desalting, cut off, etc)
Extract Storage
Extract Relocation/Shipping
Separation Technique (Instrument, manufacturer, software, column, method, etc)
Mass Spectrometry (Instrument, model, software, ionization, mass analyzer, acquisition)
NMR
Data transformation (mzML, netCDF, etc)
Data pretreatment, treatment and analysis
Identification
Protocols
FAIR
20082000 2013 20162007

15. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
VIVC ID
ChEBI ID
FAIR
20082000 2013 20162007

16. Repositories: MateboLights
https://www.ebi.ac.uk/metabolights/
20082000 2013 2016 20202007

17. Repositories: MateboLights

18. Repositories: MetaboLights Study MTBLS55
Title
Abstract
Organism
Experimental factors
Study menu

19. Repositories: MetaboLights Study MTBLS55
Sample
collection
protocol
Extraction
protocol
Chromatography
protocol

20. Repositories: MetaboLights Study MTBLS55
Mass
Spectrometry
protocol
Data
transormation
protocol
Identification
protocol
Analysis
protocol

21. Metabolite annotation
Sumner et al. Metabolomics 2007
2007
Standards
2000

22. 20082000 2013 2016 20202007
Metabolite annotation

23. Repositories: MetaboLights Study MTBLS55

25. Repositories: MetaboLights Study MTBLS55

26. Repositories: MetaboLights Study MTBLS55

27. Repositories

28. # year Method(s) Institute Samples Size (GB) Views Download
1 2019 LC-MS/MS FEM (Italy) Grape 2,9 0 3
2 2019 HS-HPMS-GS-MS Beijing (China) Grape 5,56 0 0
3 2019 LC-MS/MS FEM (Italy) Grape 1,24 0 0
4 2017
LC-MS/MS &
LC-Qtof-MS
FEM (Italy)
Grape 54,56 133 7
5 2017 NMR Italy Grape 6,21 115 55
6 2017 GCxGC-Tof-MS FEM (Italy) Grape Must 47,60 182 170
7 2015 GCxGC-Tof-MS FEM (Italy) Grape 101,05 18 98
8 2014 LC-QTof-MS FEM (Italy) Grape 5,89 9 151
9 2014 LC-QTof-MS FEM (Italy) Wine 13,17 16 505
10 2014 LC-DAD FEM (Italy) Grape 1,84 13 3
11 2013 LC-QTof-MS Verona (Italy) Grape 0,06 12 37
12 2013 GC-MS Davis (USA) Wine 133 0
13 2010 NMR Bordeaux (France) Grape
MetaboLights 10/614 studies about vitis+grape+wine (1,6 %)
20082000 2013 2016 20202007
Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
https://www.omicsdi.org/
https://www.ebi.ac.uk/metabolights/

29. 20082000 2013 2016 20202007
Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
vitis + metabolomics (145)
grape + metabolomics (224)
wine + metabolomics (263)
www.scopus.com

30. Introduction to FAIR principles about
Data, Metadata and Protocols in Metabolomics
Data producers: Make more data public available
Use IDs and Ontologies
Public Repositories: Make data upload more user friendly
Curation
Add tools for data analysis and data fusion
Funding agencies: Make mandatory data availability
Give extra funding for that
Bioinformatics (data re-users): Cited
Give feedback
Journals: Ask to make datasets public available
Offer discount
Instrument producers: Make raw file smaller
Produce tools that helps
Institutions: Courses
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