Rob Vreeken deel 2

3D Data Orientation (LC + IMS + MS)
…presentation of multi dimensional data
Retention
Retention
Time
Time
Mass
Mass
Mobility
Drift
UPLC/IMS/TOF Lipid analysis
RT_LCIM ST OF5.raw : 1
Lipids
Lysos
TAG’s
Chotesteryl
esters
RT_LCIMSTOF5.raw : 1
PEG
Apex 4D detection of ions using
UPLC/IMS/TOF
RT_LCIMSTOF5.r aw : 1
TIC
2D plot
showing drift
time v.s RT
Drift Time plot
All combined
spectra
RT_LCIMSTOF5.raw:1
*Red dots and sticks denotes
Apex 4D peak detection
An extra dimension with IMS
PC 34:2 (many possible combinations)
RT_LCIMSTOF5.r aw : 1
XIC for PC 34:2 m/z 758.58
Same m/z but significantly
different drift times specially
for co-eluting peaks
RT_LCIMSTOF5.raw:1
An extra dimension with IMS –Let’s
Zoom in
PC 34:2 (many possible sn-1 and sn-2 combinations)
Up
to
ca
.
50
00
co
m
po
un
ds
pe
rr
un
!!
RT_LCIMSTOF5.r aw : 1
RT_LCIMSTOF5.raw:1
Example 3: Identification of metabolites
using fragmentation trees
MS1
MS2
MS3
MS4
MSn experiment
fragmentation tree
(fragment masses)
NanoMate(Advion)-LTQ Orbitrap XL (Thermo)
Piotr Kasper, Miguel Rojas-Cherto, Justin v/d Hooft
fragmentation tree
(elemental formulas)
Identification: assignment
• identification of a known metabolite
(its MS tree is included in the database)
MSn
compare
Full MSn found
in database!
ID
Collaboration between Leiden University, TNO, Wageningen University
identification: structure elucidation
• identification of an unknown metabolite (not in database)
MSn
compare
NMR, MSn prediction,
biological evidence …
for ID verification
ID
candidate
rejection
not in database but
similarities to sub-trees found
structure
generation
+ elemental
composition
Julio Pieroncely, Miguel Rojas-Cherto
Collaboration between Leiden University, TNO, Wageningen University
Content
• What and Why in metabolomics?
• Netherlands Metabolomics Centre
• Examples:
• Amine profiling
• Lipid profiling
• Metabolite Identification
• Future developments
• Acknowledgements
NMC will result in
• Breakthroughs in Technology
NANOBOTS Single cell
metabolomics?
– Standardized quantitative methods for 1001000’s of identified compounds
– Miniaturization & less invasive sampling (single
cells, sampling pills etc)
• Breakthroughs in Biology
Microscopic machine roaming through
the body
Photographer Coneyl, reproduced courtesy of The Novartis and The Daily
– Improved phenotyping & insights into basic
Telegraph Visions of Science Photographic Awards.
mechanisms by proper models
– What are pathways, what are networks, what is
system-wide regulation, what is homeostasis?
– ‘Back’ to physiology
– From correlation to causation
• Breakthroughs in BioTech
– Predictive biomarker profiles
• responder/non-responder, safety & efficacy, risk of disease, Integration
diagnostics & intervention
– Design better microorganisms, plants, seeds
• Optimize to synchronize & guarantee the moment of harvesting
• Support improving seeds for better plant quality
• Etc.
Collaboration and open innovation is key.....
.....and what we want to achieve
From knowledge to market
Health Insurances
Biomarkers
for health
Samples
Nanofabrication
Food industry
Pharma
Demonstration &
Competence Lab
Technology
breakthroughs
New tools
System
therapeutics
Applications
Clinics
Chip
analyzer
LCxLC
interface
Spin off
MS
interface
Diagnostic
devices
Phenotyping
device
Biotechs
Instrument
manufactures
Patients
From knowledge to market
Technology
breakthroughs
NMCtools
New
Applications
From knowledge to market
NMC
System
therapeutics
Conclusions
•
Boost of technology (new instrumentation and open innovation) and its
application result in new insights and better understanding of nature
•
This tough requires a broad consortium, combination industry & academia
very beneficial
(continuous development & application of technology in common research
projects)
•
Transfer of technology platform
(various models, spin-off)
•
NMC aims to initiate international
metabolomics consortium
•
Interested? Contact us!
More info: www.metabolomicscentre.nl
Acknowledgement
Thomas Hankemeier, Jan van der Greef, Heiko van der Linden, Theo Reijmers, Rob Vreeken,
Adrie Dane, Frans van der Kloet, Marek Noga, Maya Kochman, Miguel Rojas, Piotr Kasper,
Toshi Mikami, Alexander Tempels, Eduard van Wijk, Bea Reeuwijk, Gerwin Spijksma, Faisa
Guled, Iryna Paliukhovich, Jorne Troost, Jose Castro-Perez, Narmin Ismail, Willem Engel,
Maud Koek (TNO) Kjeld Janssen, Jurre Kamphorst, Peter Lindenburg, Harmen Draisma, Jos
Quist, Jiajie Li, Shanna Shi, Herman van Wietmarschen, Julio Peironcely, Jiangshan Wang,
Chunxiu Hu (cooperation with prof. Xu, Dalian), Ronnie van Doorn & Bernd van Buuren (MT
NMC)
CAS KNAW Joint Programme
www.metabolomicscentre.nl