Facilitate Metabolite Biomarker Discovery Using HRAM … · Facilitate Metabolite Biomarker Discovery Using HRAM LC-MS ... (AMP) 178.07244 232 ... Facilitate Metabolite Biomarker

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Facilitate Metabolite Biomarker Discovery Using HRAM LC-MS-MS Approach on an Orbitrap Mass Spectrometer

Osama Abu-Nimreh

CMD Sales Support Specialist

MECEC , Dubai

2

Metabolomics- Insights to Biology

Environment

Microbiome

DNA Genomics – 22,000 genes

Biological potential

RNA Transcriptomics – 100,000 transcripts

Response to conditions

Proteins Proteomics – 1,000,000 proteoforms

Biological Function

Metabolites

Lipids

Metabolomics >5,000 compounds

Lipidomics >30,000 species

Physiological state/phenotype

3

Diverse Applications in Human Health and Disease Research

Cancer

Aging

Biomarker Discovery

Infectious Diseases

Inflammation/ Immunology

Cardiovascular

Personalized Medicine

4

Biomarker Discovery Using Untargeted Metabolomics Profiling

Sample A1 Sample A2 Sample A3 Sample B1 Sample B2 Sample B3

Group A

Group B

• Study Design - ex: Normal vs. disease,

Different time course

• Sample Preparation and LC/MS Analysis - Extracting metabolites from samples

LC/MS/MS analysis

• Identify Unknown Metabolites - Propose name, chemical composition and

structure of unknown compounds

• Differential Analysis and Statistical

Analysis

- Detect metabolites of interests

(putative biomarkers)

Require High Coverage of a metabolome

5

• Diversity in structures and physical chemical properties

- Require multiple technologies to capture a

metabolome

• Many isomeric and isobaric species

- Require high resolving power for correct ID

• Very low to very high concentrations

- Require High sensitivity and wide dynamic

range

• No single database to identify all unknown metabolites

- Require extensive library or fragment ion

prediction based on compound structure

Challenges for Untargeted Metabolomics

6

Ultra high resolution, fast scan speed and good sensitivity

Excellent mass measurement accuracy and precision

High quality MS/MS spectrum (MSn capability)

Thermo Scientific™ Orbitrap™ Mass Spectrometer Portfolio

Thermo Scientific™ Q Exactive™ hybrid

quadrupole-Orbitrap mass spectrometer

Q Exactive HF

Thermo Scientific™ Orbitrap

Fusion™ Tribrid™ mass spectrometer

Orbitrap Fusion

Thermo Scientific™ Orbitrap™ Elite High-Field

Orbitrap Hybrid Mass Spectrometer

Thermo Scientific™ Orbitrap Fusion™

Lumos™ Tribrid™ Mass Spectrometer

Orbitrap Fusion Lumos

140,000@m/z 200

12 Hz @15,000 240,000@m/z 200

18 Hz @17,500

500,000@m/z 200

18 Hz @15,000

500,000@m/z 200

20 Hz @15,000

Q Exactive

Q Exactive Plus

7

Orbitrap: Unmatched Resolution vs. QTOFs

0

50000

100000

150000

200000

250000

300000

350000

100 200 300 400 500 600 700 800 900 1000

Resolu

tion (

FW

HM

)

m/z

Q Exactive MS

Q Exactive HF MS

QTOFs

8

Resolving Isobaric Metabolites with Orbitrap High Resolution

9

PositiveMode20130518092831 #539 RT: 1.44 AV: 1 NL:T: FTMS + p ESI Full ms [100.00-212.08]

151.05 151.06

m/z

0

20

40

60

80

100

Rel

ativ

e A

bund

ance

R=120k


151.05 151.06

m/z

0

20

40

60

80

100

Rel

ativ

e A

bund

ance

R=60k


151.05 151.06

m/z

0

20

40

60

80

100

Rel

ativ

e A

bund

ance

R=240k


151.05 151.06

m/z

0

20

40

60

80

100

Rel

ativ

e A

bund

ance

R=30k

High Resolution is Essential for Fine Isotopic Pattern Determination & Isotopic Labeling Experiments

• L-Methionine C5H11NO2S (+ mode)

PositiveMode20130518092831 #656 RT: 2.64 AV: 1 NL: 1.48E8T: FTMS + p ESI Full ms [100.00-212.08]

150.0 150.5 151.0 151.5 152.0

m/z

0

10

20

30

40

50

60

70

80

90

100

Rel

ativ

e A

bund

ance

150.0584R=627006

151.0618R=621502

152.0542R=601802


151.05 151.06

m/z

0

20

40

60

80

100

Rel

ativ

e A

bund

ance

R=500k

0.7ppm

C5H11NO2S +H: C5 H12 N1 O2 S1 p(gss, s/p:40) Chrg 1 ...

150.0 150.5 151.0 151.5 152.0

m/z

0

10

20

30

40

50

60

70

80

90

100

Rel

ativ

e A

bund

ance

150.0583R=499553

151.0617R=499368

152.0541R=499443

R=500,000

0.0ppm

C5H11NO2S +H: C5 H12 N1 O2 S1 p(gss, s/p:40) Chrg 1 ...

151.050 151.055 151.060 151.065

m/z

0

20

40

60

80

100R

elat

ive

Abu

ndan

ce

151.0617

C413CH12O2NS

151.0625

C5H12O17ONS

151.0646

C5H112HO2NS

151.0577

C5H12O2N33S

151.0554

C5H12O215NS

Observed

Simulated

A0

A1 A2

10

Resolving Isotopically Labeled Peaks with Orbitrap High Resolution

ASMS poster, M490

Anastasia Kalli et. al.

Only Orbitrap MS Can

Confidently Track

Isotopologues of

Metabolites in Complex

Samples for Quantitative

Flux Analysis

11

Orbitrap: Unmatched Mass Accuracy vs. QTOFs

-10

-5

0

5

10

-10

-5

0

5

10

Scan

Err

or

(pp

m)

Scan

Err

or

(pp

m)

Q ToF

Error Range = 17.65 ppm !

Q Exactive

Error Range = 1.55 ppm

12 scans 12 scans

Data From Bristol-Myers Squibb Company

Accuracy and stability of mass measurement are crucial for metabolite identification

QTOF MS: Company X

Orbitrap MS: Q Exactive LC-MS

12

Orbitrap: Unmatched Sensitivity vs. QTOFs

Amino Acid Full Scan LOQ

Data courtesy from Stanford University

13

Orbitrap: Triple Quadrupole MS Comparable Sensitivity and Linear Dynamic Range

R2 = 0.9962

0.2–20000 pg spiked in plasma

(1 fmol–100 pmol on column)

QE HF

Quantitation of Citric Acid achieved at low fmol sensitivity using full scan MS

Five Orders of Magnitude Linear Dynamic

Range

14

Quantitation of 17:0-14:1 PC achieved at attomole sensitivity using targeted MS/MS method

Orbitrap: Triple Quadrupole MS Comparable Sensitivity and Linear Dynamic Range

17:0-14:1 PC spiked into 500 ng Bovine

Heart Lipid Extract

0.02 pg – 2000 pg on column

QE HF

Log (Area)

Amount, pg

Five Orders of Magnitude Linear

Dynamic Range

15

Thermo Scientific™ Compound Discoverer 2.0™

Complete small molecule structure identification in a Next Generation platform.

Compound Discoverer 2.0™ focuses on workflows for Discovery Metabolomics: Fundamental Research, Biomarker Discovery, Pharma, Environmental Research, Forensics, Foodomics, etc.

16

Compound Discoverer 2.0: Destination Unknowns

Unknown Analysis

Identification

Statistics

mzCloud

ChemSpider

User Database{

17

What is mzCloud ? www.mzCloud.org

• Cloud-based HRAM MSn

spectral libraries of small

molecules

• Base on Mass Frontier

technology

• Search, Compare, Annotate

Growing Every Day!

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Streamlined Untargeted Metabolomics Workflow Using Orbitrap MS and Compound Disocverer 2.0

Collect Urine, Plasma

Cell, Tissue etc…

Hypothesis,

Candidate

Biomarkers

Statistical analysis Trends Pathways

Collect HR LC/MS

profiles

Lists of

components Data processing

Metabolites

t-MS/MS

Ready for injection

samples

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Case Study: Discovery Diabetes Marker of Zucker Rat Plasma Using LC-HRAM Orbitrap MS

Obese (Zucker) vs. Lean

Rat

Lean Obese (Zucker)

Sample 1 Sample 2 Sample 3 Sample 1 Sample 2 Sample 3

Pos/Neg ion ESI

Vaporizer temp = 450°C

MS Resolution = 140K

Mass range: 67-1000 Da

Run Time = 15 min

Top5 dd-MS2 at 17.5K Resolution

Hypersil GOLD™ HPLC columns

150 x 2.1 mm, 1.9 μm

Column temp.: 55 oC

Injection vol: 5 µL

Mobile phase:

A = 0.1% formic acid in H2O,

B = 0.1% formic acid in MeOH

Flow rate: 0.45 mL/min

UltiMate™ 3000

Q Exactive™ Plus

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Identifying Unknowns: mzCloud

Automatically assign best MS and MS/MS spectra

in your dataset based on RT, intensity, adduct


21 Proprietary & Confidential

Compound name and structure

Spectrum match

Raw file

Reference (mzCloud)


22

Reproducible High Quality LC-MS Data For Label Free Differential Analysis

[M+H]+

0.54 ppm

[M+Na]+

0.43 ppm (A)

(B)

(C)

QC with IS = d5-hippuric acid C9H4D5NO3

23

Compound Discoverer Results Review of Interested Metabolite

(A) Compound of interest

(B) XIC (E) isotope match

(C) Predicted formula

(F) Trend

(D) MS spectra

24

Advanced Features and Functionalities

Checked (checked compounds will be

carried through all analysis)

(G) Filter panel (H) Volcano plot

178.07244 232.08295

137.04582

119.03501

212.01514 225.0546656.96513 114.11062

243.06592137.04587

250.09351

287.05444

304.02682

348.02307

331.04495

97.02841

97.02835348.07001

348.07036

136.06183

136.06177

50 100 150 200 250 300 350

m/z

-6

-4

-2

0

2

4

6

Inte

nsity

[co

un

ts] (1

0^6

)

RAWFILE(top): pooled_top2_Ex6s_100ms_1E4, #701, RT=1.111 min, FTMS (+), MS2 (HCD, DDF, [email protected], z=+1) REFERENCE(bottom): mzCloud library C10 H14 N5 O7 P Adenosine 5'-monophosphate FTMS (+) MS2 (HCD [email protected])

mzCloud Library entry

query entry

(I) (J) (K) Automated

identification pathways mapping

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Finding Potential Markers With Less Effort

(A) Fatty Lean Ratio

(B) p-value

150 compounds were automatically assigned with

mzCloud library through MS/MS match

16 metabolites show significant changes (p-

value<0.05, fold change >1.5)

26

Examples – Adenosine 5’-monophosphate (AMP)

178.07244 232.08295

137.04582

119.03501

212.01514 225.0546656.96513 114.11062

243.06592137.04587

250.09351

287.05444

304.02682

348.02307

331.04495

97.02841

97.02835348.07001

348.07036

136.06183

136.06177

50 100 150 200 250 300 350

m/z

-6

-4

-2

0

2

4

6

Inte

nsity

[co

un

ts] (1

0^6

) RAWFILE(top): pooled_top2_Ex6s_100ms_1E4, #701, RT=1.111 min, FTMS (+), MS2 (HCD, DDF, [email protected], z=+1) REFERENCE(bottom): mzCloud library C10 H14 N5 O7 P Adenosine 5'-monophosphate FTMS (+) MS2 (HCD [email protected])

Fatty Lean

Box-Plot

mzCloud Reference

Query (Raw data)

AMP

Fold change 7.5

P value 5.8e-6

MS/MS spectra match of raw data vs. mzCloud

27

An Overview Of All Detected Metabolites With Biological Relevance

AMP related metabolites

mapping in the pathway

All Metabolic pathways that had

been hit in the analysis

28

Fa

tty

Le

an

Groups

3.5

4.0

4.5

5.0

5.5

Are

a (

10

^6)

Acylcarnitine Subclass Were Upregulated In Obese Zucker Rats

Fa

tty

Le

an

Groups

12

14

16

18

20

22

Are

a (

10

^6)

Propionylcarnitine Palmitoylcarnitine

Fa

tty

Le

an

Groups

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

Are

a (

10

^6)

Hexanoylcarnitine

Fa

tty

Le

an

Groups

300

400

500

600

700

800

900

Are

a (

10

^3)

DL-Carnitine Acetyl-L-carnitine

Fa

tty

Le

an

Groups

6

7

8

9

10

11

12

13

14

15

Are

a (

10

^6)

Mihalik S.J.; Obesity (Silver Spring). 2010 Sep;18(9):1695-700

mzCloud Results

Elevated > 2-fold

In Fatty rat plasma

29

Summary: The Exciting Scientific Metabolomics Solutions We Offer

Metabolomics

challenges

Compound Discoverer 2.0 mzCloudTM

GC/Q Exactive MS

Ion Chromatography/QE

OrbitrapTM Technology

Multi-omics Integration and Pathway partner

Wang, J. Anal. Chem. 2015, 87, 6371

Wang, J. Anal. Chem. 2014, 86, 5116

Peterson, A. Anal. Chem., 2014, 86, 10036

Peterson, A. Anal. Chem., 2014, 86, 10044 GC IC

30

Acknowledgements

Junhua Wang

Ralf Tautenhahn

Tim J. Stratton

Caroline Ding

David A. Peake

Reiko Kiyonami

Mark Sanders

Julian Saba

Andreas Huhmer

Ken Miller

Dr. Robert Mistrik

The mzCloud Team

Dr. Kévin Contrepois

School of Medicine -

Department of Genetics

31

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Facilitate Metabolite Biomarker Discovery Using HRAM … · Facilitate Metabolite Biomarker Discovery Using HRAM LC-MS ... (AMP) 178.07244 232 ... Facilitate Metabolite Biomarker