Metabolomics and Lipidomics Approaches for Biomedical

©2015 Waters Corporation 1

Metabolomics and Lipidomics Approaches for Biomedical Research and Biomarker Discovery

Giuseppe Astarita

Principal Scientist, Health Sciences

Waters Corp, USA

Waters Users Meeting ASMS 30 May, 2015

In situ; Imaging Scanning along x and y axes using high-res instruments (spatial information; molecular histology)

Targeted Monitoring selected ions in high-res or nominal mass (quantitative; sensitive; requires internal standards)

Structural Elucidation High-res instruments with fragmentation capabilities (chemical structure)

O

O

HO

R1 O ON

+

P

OH

O

O

R2

Phosphotadylcholine (PC)

sn-1

sn-2

sn-1-H20

sn-2-H20

Untargeted Scanning for differences using high-res instruments (semi-quantitative; statistics-based; hypothesis-generating)

1 2 3 4

Metabolomics Approaches

Measure (Mass Spectrometry)

Separate (Chromatography; Ion Mobility)

Process and Mine (Informatics and Statistics)

Metabolomics and Lipidomics

Metabolomics in Systems Biology

Gene function Diet Environmental exposure

Typical Metabolomics Applications

Disease

WT/KO cells Transgenic mice Treated mice Human subjects

PNAS, 2015 PLOS ONE, 2014 J Proteome R, 2014 In Preparation


Poster 202 – Metabolomics: Untargeted Metabolite Profiling II A mass-spectrometry-based metabolic phenotyping strategy to investigate the molecular response to ionizing radiation

Occupational exposure (medicine,

manufacturing and construction)

Medicine (research, diagnosis and therapy)

Airline/Space Travel

Radiation Exposure

Hiroshima Nagasaki

Fukushima Daiichi

Others:

Three Mile Island, US

Goiania, Brazil

Kozloduy, Bulgaria

Chernobyl

Nuclear and Radioactive Accidents

Health Effects of Radiation Exposure

•Cancer

•Cardiovascular Disease

•Cognitive decline

Molecular Effects of Radiation Exposure

DNA

Proteins

Lipids/Metabolites


Aims of the study

2. Determine biomarkers or biosignatures associated with radiation exposure

1.Investigate the biochemical mechanisms underlying radiation exposure

Laiakis E. et al, J Proteome Res. 2014 Sep

Blood collection

LC tandem MS

Oxylipin Profiling

SPE clean up

LC/TOF MS

Global Metabolic Profiling

Serum preparation

1

2 3 4

Irradiated Sham Control

Biocrates kit Liquid-liquid

Targeted Metabolic Profiling

Internal standard

Endogenous metabolite

Study Design


MS Imaging

Cryostat sectioning




O

O

HO

R1 O ON

+

P

OH

O

O

R2


sn-1

sn-2

sn-1-H20

sn-2-H20


1 2 3 4


Metabolomics: UPLC Separation

Paglia G.et al. Anal Chem 2014

Lipidomics: UPLC Separation

ChoE & TG PC, SM, PG, PE

lysophospolipids SM, DG, ChoE

PC, PG,PI, PS, PE

Free Fatty Acids

Astarita G., et al. PLOS ONE 2014

Orthogonal Coordinates

ChoE & TG

PC, SM, PG, PE

lysophospolipids

Damen C., et al. Journal Lipid Research 2014

Paglia G.et al. Anal Chem 2015

FAIMS

DTIMS

Ion

mo

bility d

rift

tim

e (µ

s)

TWIMS

a

b

c

Ion Mobility Separation: Hybrid Q-TOF

Poster 649 – Ion Mobility: Small Molecule and Metabolomics The analysis of Bile Acids: Enhancement of specificity using an Ion Mobility-TOFMS based approach

Composite ion map after peak picking

Individual ion maps

Data alignment and peak picking

ANOVA filtering and Multivariate Statistics

Database search

Filtering by ANOVA P value

Control Radiation

Control

Radiation

Tentative Identifications

1.

2. 3.

4.

5.

Data Processing and Mining


0

20

40

60

80

100

120

140

160

180

5 6 7 8 9 10 11 12 13 14 15

ide

nti

ficati

on

s

ppm m/z error

HMDB

In house database no RT

In house database with RT <0.6 min

Database Search using Orthogonal Coordinates

Database Search using Orthogonal Coordinates

HDMSE

<25 fragments HDMSE High Energy

HDMSE Low Energy 750.5422

750.5422

303.2324 (FA 20:4)

303.2324 (FA 20:4)

%

%

m/z 200 1400

With Ion mobility separation

Co-eluting ions

Fragments Transferred to TOF-MS

Fragmentation

m/z Tentative ID ANOVA (p value) Max Fold Change Method

818.6050 PC(P-18:0/22:6) 5.12E-06 8.0 Reversed phase






703.5747 SM(d18:1/16:0) 2.09E-04 12.5 Reversed phase

162.1117 Carnitine 1.50E-02 1.7 HILIC

166.0861 Phenylalanine 1.53E-02 1.2 HILIC

Global Metabolic Profiling




O

O

HO

R1 O ON

+

P

OH

O

O

R2


sn-1

sn-2

sn-1-H20

sn-2-H20


1 2 3 4


Targeted Metabolic Profiling:

Metabolomics kits

Metabolite group No. of metabolites

Amino acids and Biogenic

amines

40

Acylcarnitines 40

Lyso-phosphatidylcholines 14

Phosphatidylcholines 74

Sphingomyelins 14

Hexose 1

Total 183

+

Poster 401 – Metabolomics: Quantitative Analysis Improved performance of targeted metabolome analysis with Waters Xevo® TQ-S and Xevo® TQ-S micro instruments

Control Radiation

Co

nc

en

tra

tio

n (

µM

)

PC

aa C

34:1

PC

aa C

36:5

PC

aa C

38:5

PC

aa C

38:6

PC

aa C

34:4

PC

aa C

36:6

0

1

2

1 0

4 2

7 4

1 8 0

3 3 0

4 8 0 C o n tro l

R a d ia tio n

***

***

******

******

Co

nc

en

tra

tio

n (

µM

)

PC

ae C

36:4

PC

ae C

36:5

PC

ae C

38:4

PC

ae C

38:5

PC

ae C

38:6

PC

ae C

32:1

0

2

4

6

8

1 0

C o n tro l

R a d ia tio n

***

***

***

***

***

***

Diacyl PCs Ether PCs

Component 1 (32.2%)

Com

ponent

3

(11.5

%)

Targeted Metabolic Profiling


Arachidonic acid

Diacyl PC

Metabolites

?

PLA2

Data Integration: Molecular Effects of Radiation

Plasmalogens Oxidation

Aldehydes

Eicosanoids: Bioactive Oxygenated PUFAs

Omega-6 metabolites: pro-inflammatory

Omega-3 metabolites: anti-inflammatory

Plasma sample

Add internal standard mix

Load

Inject into UPLC/MS-MS

SPE clean up

Multiplexed Assay for Eicosanoids Profiling

Selected Lipid

Internal Standard

Control Radiation

Co

nc

en

tra

tio

n (

µM

)

12-H

HT

rE

11-H

ET

E

14,1

5-D

iHE

TrE

8-H

ET

E

12-H

ET

E

0

5

1 0

1 5

2 0

2 5

5 0 0

1 0 0 0

1 5 0 0C o n tro l

R a d ia tio n

******

***

***

***C

on

ce

ntr

ati

on

(µ

M)

17,1

8-D

iHE

TE

14,1

5-D

iHE

TE

9-H

OT

rE

0

1

2

3

5

1 0

1 5

C o n tro l

R a d ia tio n*

*

***

Omega-6s Omega-3s

Component 1 (26.9%)

Com

ponent

3 (

24%

)

FA 18:3

FA 20:5

Eicosanoids Profiling


Pathway Analysis

Omega-6 metabolites: pro-inflammatory

Omega-3 metabolites: anti-inflammatory

8-HETE

Arachidonic acid

Diacyl PC

Metabolites

?

PLA2

Data Integration: Molecular Effects of Radiation

Data Fusion: Biosignature of Radiation Exposure

Top metabolites correlated with the irradiated phenotype

Total Body Irradiation

Synapt G2 Si

Xevo TQ-S

Untargeted Metabolomics

Untargeted Lipidomics

Targeted Metabolomics

Pre ~6hr

~24hr

Peak Picking

Statistical Analysis

Progenesis QI

Validation through tandem MS

or fragment matching through

online databases

TargetLynx

for quantification

Pathway annotation

HMDB, KEGG, Lipidmaps

Statistical Analysis

and pathway assignment

Serum

Pre, 6hr, 24hr

SPE clean up

TBI received prior to hematopoietic stem cell transplant (n=15)

In vivo responses to total body irradiation (TBI) in patients

Slide from Evagelia C. Laiakis

9-HODE

13-HODE 13-OxoODE (13-KODE)

12(13)-EpOME

9(10)-EpOME 9,10-DiHOME

12,13-DiHOME

5-HETE

9-HpODE 9-OxoODE

9,12,13-TriHOME 9,10,13-TriHOME

13-HpODE

9,12,13-TriHOME

Linoleic acid (LA)

Dihomo- -linolenic acid (DGLA)

15-HETrE PGH2

TXB1

PGI1

PGF1

PGD1 PGE1

Arachidonic acid (AA)

PGG2

PGH2

PGF2

15-keto-PGF2

15-deoxy-12-PGJ2

PGE2

PGA2

PGC2

PGB2

TXA2

TXB2

PGD2

PGJ2

12-PGJ2

15-oxo-ETE

15-HpETE

15-HETE

12-HETE 11-HETE 8-HETE

5-HpETE

LXB4

LTA4

LTB4

LXA4

LTC4

LTD4

LTE4

5-oxo-ETE

5(6)-EpETrE 8(9)-EpETrE 11(12)-EpETrE 14(15)-EpETrE

5,6-DiHETrE 8,9-DiHETrE 11,12-DiHETrE 14,15-DiHETrE

LOX CYP450

LOX

COX

COX

CYP450

LOX

13,14-dihydro-15-keto PGE2

bicyclo-PGE2

12-HHTrE

HETEs

non enzymatic

12(S)-HpETE

12,13-DiHODE 9-HOTrE

Preliminary Results in Human Subjects

Pre 6hr

24hr

0

100000

200000

300000

Linoleic acid

No

rma

lize

d A

bu

nd

an

ce p=0.0057

Pre 6hr

24hr

0

5000

10000

15000

20000

25000

Dihomo-gamma-linolenic acid

No

rma

lize

d A

bu

nd

an

ce

p=0.0208

Slide from Evagelia C. Laiakis


Conclusions

Integration of multi-platform lipidomics data highlighted new biochemical pathways associated with radiation exposure

The multiplexed assay identified marked alterations in a subset of pro-inflammatory lipid mediators

The untargeted lipidomics approach uncovered a differential metabolism for diacyl phospholipids and plasmalogen

-1.0

-0.5

0.0

0.5

1.0

-0.010 -0.009 -0.008 -0.007 -0.006 -0.005 -0.004 -0.003 -0.002 -0.001 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.009 0.010

p(co

rr)[1]P

(C

orrelatio

n)

CoeffCS[2](Group) (X Effects)

S-Plot (Group 1 = -1, Group 2 = 1)

EZinf o 2 - 20120911_Liv erPos1 (M4: OPLS-DA) - 2012-09-24 15:39:03 (UTC-5)

Fusion of multi-platform data highlighted a

metabolomics biosignature associated with

exposure to radiation exposure

Methodological References: Untargeted

Methodological References: Targeted


Acknowledgements

Thomas Hankemeier Rob Vreeker

Katrin Strassburg

Albert Joseph Fornace Evagelia C. Laiakis

Jim Langridge Rob Plumb

Emmanuelle Claude Jeff Mazzeo

Ralf Bogumil Cornelia Roehring

Therese Koal

Documents

Metabolomics and Lipidomics Approaches for Biomedical