Analysis of Lipid Metabolites = Lipidomicsresearch.med.helsinki.fi/corefacilities/proteinchem/Lipidomics Transmed 19 10 2012.pdf · Outline of the talk • What is Lipidomics? •

Analysis of Lipid Metabolites

= Lipidomics

Pentti Somerharju

Transmed 11.10.2012

Outline of the talk• What is Lipidomics? • Where is lipidomics needed?• Lipid classes and their functions• Why mass-spectrometric analysis?• Targeted or nontargeted analysis?• How to improve selectivity of detection? • Data analysis and interpretation• Dynamic lipidomics (study on lipid metabolism)• Glycerophospholipid homeostasis

– Regulation of synthesis– Regulation of degradation– Coordination by superlattice formation?

Lipidome is part of the metabolome

DIET

Functional Lipidomics = How other molecules affect the lipidome and vice versa

Where is lipidomics needed?Biology

Functions of lipids?Regulation lipid composition of membranes?

ClinicsSearch of diagnostic/predictive markersSearch of drugs targeting lipid disorders

IndustryModification of fats and oilsQuality control

Significance of lipidomic data?

Very similar changes in lipidome when P53 or ApoE is knocked out

=>Changes in lipidome can be nonspecific!

”False biomarkers” also when the number of lipids analyzed exceeds the number of samples (patients)

Many confounding factors: diet, gut microbiota, physical activity, age, genetic background etc

Targeted analysis• When you know what you are looking for

(e.g. studies on lipid homeostasis)• Selective detection (MS/MS or LC-SRM)

Nontargeted analysis• When you do not know…(search for disease markers/biomarkers)• Nonselective detection (LC-MS)

Mammalian Lipid classes and their main Functions

Glycerophospholipids

>10 classes (PC, PE, PS, PI, PA etc)

Each class consists of numerous species due to different fatty acid combinations

=> Thousands of different species possible!

Functions:Main structural components of membranesSecond messengers in signal transductionRegulators of membrane traffickingetc

O

OO

O

HCH2C CH2

O

PO

O

ON

H

H

H

H

HHH

H

HH

HH

H

Phosphatidylcholine

Apolar (neutral) lipids

Fatty acidsStructural componets of other lipidsEnergy source/storagePrecursors of eicosanoids etc

Acylglycerols (TG etc)Fatty acid storage and transportHundreads of species possible

Cholesteryl estersStorage forms of cholesterol

O

O

O

O

HCH2C CH2

O

O

Lactosylceramide

O

O

HNHC

CH2

O

C OH

CH

O

H

H

OH

H

O

H

H

OH

O

OH

H

H

OH

H

O

HO HH

OHGlygosphingolipids

Tens of different classes (head groups)Many different fatty acid=> Hundreads of possible species

FunctionsStructural component of membranesCell-cell regognitionSignal transduction

Other lipid classes

Sterols (cholesterol etc)Structural components of membranesPrecursor or steroid hormones

Eicosanoids (prostagandins etc)Signaling

Prenol lipids Membrane anchors in some proteins

A mammalian cell may contain thousands of differerent lipid species!

The biological challenge: Why?

Each lipid species has a specific function?

No..most lipids act in an ensemble!

The Analytical challenge

How to quantify so many species with so different properties and present at sodifferent concentrations?

....with Mass Spectrometry!

Advantages of mass-spectrometry

Conventional analysis (PL)

1. Lipid extraction 2. Separation of lipid classes

by TLC or HPLC3. Separation of molecular

species by HPLC4. Treatment by phospholipase A25. Analysis of fatty acids by GC 6. Data processing

Slow (several days)Low sensitivityPlenty of manual work

MS-analysis

1. Lipid extraction 2. MS/MS or LC-MS analysis3. Data processing

Fast (even less than 1 hour)Very high sensitivityCan be automated

Which ionization mode?

Electrospray (ESI)– Does not cause fragmentation – Compatible with on-line LC

Matrix-assisted laser desorption (MALDI)– Used less due to e.g. suppression effects

=> All lipids not detected

Electrospray ionization

Competition for charge => Suppression effects!

Which mass analyser?

Triple quadrupole“Workhorse”of lipidomicsAllows precursor and neutral-loss scanning

= Lipid class-specific detectionModestly (?) priced

Fourier transform or OrbitrapVery high mass resolution and accuracy Allow detailed analysis of lipid structureVery expensive!

Direct MS scanning (triple quadrupole)

Scanning

MS1 MS2Collision cell Detector

HeLa in C/M/2P 1:2:4 + 0.5mM NH4Ac

0

100

%

773.5659053

747.5251805

745.4742906

714.5022583

699.4021692685.77

18151672.4613010 701.45

8823

742.5320205

722.5014447 740.48

8765

748.5433056 761.53

29032

788.5334705

775.5415077

861.5429995790.51

22346818.5417591792.56

10744 833.459706 859.62

5838

863.6518468 885.53

14726

864.548600

887.589637

788.48

MS- spectrum of HeLa cell lipid extract

> More resolution/selectivity needed!

PIs

Means to improve resolution

• MS/MS (tandem MS)

• LC-MS (with SRM)

Lipid class -specific scanningPhospholipid class consist of species with the same polar head-group but different fatty acid combination

Phospholipid class Specific scanPhosphatidylcholines Precursors of +184Phosphatidylinositols Precursors of -241Phosphatidylethanolamines Neutral-loss of 141Phosphatidylserines Neutral-loss of 87

O

O O

O

CH

CH2

H2C O P

O

O

O X

Precursor ion scanning

Requires a characteristic, charged product ion

PC => Diglyceride + phosphocholine (+184)

FragmentationScanning Static (+184)

Quadrupole 1mass ”filter”

Quadrupole 2mass ”filter”

Collision cell(Helium or Argon)

Precursors of +184 => PC + SM

-Alkaline hydrolysis can be used to remove PCs

SM-16:0

Neutral-loss scanning

Scanning Fragmentation Scanning

Qaudrupole 1 Quadrupole 2Collision cell

Mass interval = 141

..when the characteristic fragment is uncharged

PE => Diglyceride (+) + phosphoethanolamine (141)

Selective detection of PE, PS and PI

• Martinilta kuva MS- ja muut

HeLa-cells +CTRL-siRNA + D9Chol+D4-EA+D3-Ser +HA

m/z690 700 710 720 730 740 750 760 770 780 790 800 810 820 830 840 850 860 870 880 890 900 910

%

0

100

%

0

100

%

0

100101208 Allstar 4h 9 1 (2.514) Sb (1,40.00 ); Sm (SG, 10x0.50); Sm (SG, 10x0.50) Neutral Loss 141ES+

6.66e5744.4665870

718.4288039

716.3212939

690.364887

712.328025

742.4208502

738.3120092

768.4552013

766.4485530

745.4295373

746.4221707

762.381579

800.5476617

790.4306640769.4

260924788.4

161459770.4125344

786.461259

801.5236480

802.564973 822.5

56773814.327630

101208 Allstar 4h 3 1 (3.019) Sb (1,40.00 ); Sm (SG, 10x0.50) Neutral Loss 87ES- 4.08e5788.2

407952

786.2221173

760.2156295

758.226686708.8

22382704.28871

732.315724

746.210512

761.284866 774.2

36017

842.3270773

789.2195176

810.297039790.2

54227 808.222345

834.174231812.2;44228

843.3108831

844.227259 884.1

16260896.214557

908.211330

101208 Allstar 4h 5 1 (3.123) Sb (1,40.00 ); Sm (SG, 10x0.50) Parents of 241ES- 5.18e5837.4

517529

809.4212029

795.423218

810.385502 823.3

63587835.430933

838.4212711

865.4165355

861.455440851.4

36455

866.467757 885.4

64017

PE

PS

PI

Analysis of Sphingolipids

Sphingosine Ceramide Lactosylceramide Ganglioside Sulfatide

O

O

HNHC

CH2

O

C O

CH

O

H

H

OH

H

O

H

H

OH

O

OH

H

H

OH

H

O

HO HH

OH

O

O

HNHC

CH2

O

C OH

CH

O

H

H

OH

H

O

H

H

OH

O

O

H

H

OH

H

O

HO HH

HO

O

COOH

O

HO

OH

AcHN

OH

HO

O

O

HNHC

CH2

O

C OH

CH

O

H

H

O

H

O

H

H

OH

H3SO3-

OOH

O

COOH

O

HO

OH

AcHN

OH

HO

H3SO3-

OO

HNHC

CH2

C OH

CH

OH

HHNHC

CH2

C OH

CH

OH

Ceramide and Neutral Glycosphingolipids

- Precursors of sphingosine (m/z +264)

Ceramides

Glucosylceramides

24:1

Sulfatides

- Precursors of sulfate (m/z -97)

Quantification is not simple because intensity depends on:

Lipid head-group structureAcyl chain lengthAcyl chain unsaturationIons present (adduct formation)Detergent and other impurities (suppression)Solvent composition and instrument settings

=> Internal standards necessary!

Data analysis software is essential

LIMSALIMSA does:

Peak picking and fitting

Peak overlap correction

Peak assignment (database of >3000 lipids)

Quantification using internal standards

PAUSE

Dynamic Lipidomics: Analysis of lipidMetabolism

BiosynthesisDegradation

Precursors:

– Choline, ethanolamine, glycerol, fatty acids,– Sphingosine, monosaccharides etc

– 2H or 13C -labeled

Selective detection of headgroup-labeled PCs

D9-PC > Diglyceride + D9-Phosphocholine (+193)

7 0 0 7 5 0 8 0 0 8 5 0

Inte

nsity

m / z

P I + 1 8 4P I + 1 9 3

LC-MS/MS with selective reaction monitoring

TIC

767 => 193 (D9-PC)

758 => 184 (PC)

Time1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00

%

0

100

1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00

%

0

100

1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00

%

0

100

767.5 > 193 (d9-PC-34:2)5.46 e6

758.5 > 184 (PC-34:2)9.66 e6

TIC

Selective detection of other labeled GPLs

D6-PI = Precursors of -247

D4-PE = Neutral loss of 145

D3-PS = Neutral loss of 90

Specific labeling is easy to determine

All precursors can be present simultaneously!

How a cell maintains the phospholipid homeostatis of its membranes?

• Biosynthesis• Remodeling• Degradation• Trafficking

How are these coordinated?

Biosynthesis

Glycerol-3-P DHAP Choline

Ethanolamine

1-acyl-G-3-P 1-acyl-DHAP

PA

CDP-DG

DAG

PI

Choline-PCDP-choline

PC

CT

PE

PS

PSS1

CDP-Ethanolamine

Ethanolamine-P

PG-P

PG

CL

PSS2

+ Inositol

Biosynthesis of Glycerophospholipids

Our studies on GPL biosynthesis

PROTOCOL

Label cellular GPLs using a mix of D9-choline, D4-ethanolamine, D3-serine and D6-inositol

Load a GPL to cells using m -CD

Incubate and extract lipids

Quantify the labeled and unlabeled GPLs by MS using HG-specific scans

Introduction of GPLs to cells using Cyclodextrin

Purpose:

1. Introduction of exogenous labeled GPLs to cells

2. Perturbation of GPL homeostasis

=> Concentration of a GPL can be encreased by 30 - 400% without compromizing cell viability (Kainu et al. J. Lipid Res. 2010)

PI loading inhibits PI synthesis

0 5 10 15 20 250,0

0,3

0,6

0,9

labl

eled

/ un

labe

led

Time (h)

CTRL PI-vesicles

0 5 10 15 20 250,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

labl

eled

/ un

labe

led

Time (h)

CTRL PE-vesicles

PE loading inhibits PE synthesis

0 5 10 15 20 250,0

0,3

0,6

0,9

1,2

labl

eled

/unl

abel

ed

Time (h)

CTRL PS-vesicles

PS loading blocks PS synthesis

0 5 10 15 20 250,0

0,3

0,6

0,9

1,2

labl

eled

/ un

labe

led

Time (h)

CTRL PC-vesicles

PC loading inhibits PC synthesis

Product inhibition is specific!

But the details of the mechanism remains unknown..

Reversal on biosynthesis??

Degradation

A-type phospholipases (PLAs) are important players in GPL homeostasis because:

Boosting of the biosynthesis of a phospholipid class does not increase its cellular content

-E.g. over-expression of cytidyl transferase in HeLa cells did not increase tha amount of PC significantly (Baburina & Jackowski 1999)

…but the concentration of the deacylation product (glycerophospholine) was greatly increased

-Analogous data have been obtained for PE and PS

Which PLAs are involved?

Protocol to identify the homeostatic PLAs1. Determine which PLAs expressed in HeLa cells

Ca2+-independent PLAsiPLA-betaiPLA-gammaiPLA2-deltaiPLA2-epsiloniPLA2-zetaiPLA2-eta

+ several cPLAs and sPLAs (not considered homeostatic)

2. Knock-down each iPLA in turn using RNAi

3. Determine effects on phospholipid turnover using labeled precursors and MS-analysis

4. Purify the implicated iPLAs and determine specificity and regulation in vitro (and in vivo..)

PC turnover is 50% slower in iPLAknock-down cells

0 5 10 15 20 250.0

0.2

0.4

0.6

0.8

1.0

T 1/2 = 12.5h

CTRL siRNA iBeta siRNA

D9-

labe

led

/ Unl

abel

ed P

C

Chase (h)

T 1/2 = 18.7h

Also PE and PS turnover is decreased in iPLA -knock down cells

Similar results for iPLA-delta and -gamma

Open questions:

How do the homeostatic PLAs sense the ”proper” composition, i.e. how they are regulated?

How biosynthesis and degardation are coordinated?

Burke JE , Dennis EA (2009) J. Lipid Res. 50:S237-S242

Does iPLA- activity depend on substrate efflux propensity?

MS-based assay of PLA specificity

Protocol

•Mix the phospholipids (>100 different allowed)•Make vesicles •Add a phospholipase•Incubate and take samples at intervals •Extract lipids and analyze by MS

=> High throughput=> No matrix ambiquiety!

Effects of acyl chain length and unsaturation on hydrolysis by PLA

Mixture of 27 PC species:

- Acyl Chain lenght = 6 - 22 carbons

- Double bonds = 0 - 12 per molecule

STD = Shingomyelin

0 10 20 300,00

0,25

0,50

0,75

1,00

0

100

7 00 800 9000

100

B

[spe

cies

]/T0

T im e (m in)

E G F C 20 C 21 C 25

S TD

0 m inA

Rel

ativ

e In

tesi

ty (%

)

S TD 3 m in

m /z

Activity of iPLA- deceases with increasing substrate hydrophobicity

26 28 30 32 34 36 38 40 42 440,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

Rel

ativ

e ra

te o

f hyd

roly

sis

Total acyl chain carbons

PC-mix Hydrolysis decreases strongly with acyl chain length

Hydrolysis increases with increasing unsaturation

Substarate efflux is rate-limiting?

Efflux propensity can be determined from the rate of interbilayer translocation

1E-7

1E-5

1E-3

0,1

10

24 26 28 30 32 34 36 38 40 42 44 46

0,01

0,1

1

A

Tran

sfer

rate

(h-1)

0 1 2 4 6 8 12

B

Rel

ativ

e hy

drol

ysis

rate

Total acyl chain carbon number

How could efflux regulate homeostatic PLAs in vivo?

Superlattice Model predics that efflux propensity (chemical activity) increases abruptly

at ”critical” compositions

=> Only a limited number of “allowed” compositions !

Superlattice model

Xguest = 1/(a2 + a * b + b2)

Two-component bilyers

0.154 0. 25 0.50

Superlattices are dynamic minimum-energy structures

Regular distribution represent the lowest free energy state of the bilayer because it:

1. Allows optimal packing of different lipids in the bilayer

2. Minimizes the proximity of charged lipids

Optimimal packing of lipids with complementary shapes

Suboptimal packing Optimal packing

Minimal charge-charge repulsion

Excess of lipid A => Enhanced efflux (fugality)

=> Hydrolysis of by a homeostatic PLA

Regulation of homeostatic phospholipases by Superlattice formation?

Excess of a phospholipid A => Increased chemical activity of A

=> Increased feed-back inhibition of the synthetic enzyme

Regulation of biosynthetic enzymes by Superlattice formation

SL-based regulation of synthesis and degradation

- Simple mechanism that minimises compositional fluctuations

Synthesis PC Degradation Synthesis PE Degradation

PC-Regulator PE- Regulator

PS-Regulator PI- Regulator

Synthesis PS Degradation Synthesis PI Degradation

Conclusions

Heavy-isotope –labeled precursors combined with Mass spectrometry is a superior tool to study GPL metabolism

Feed-back -inhibition by the end product seems to regulate the biosynthesis of major GPLs

Substrate efflux propensity could regulate the activity of homeostatic PLAs

Superlattice formation could coordinate synthesis and degradation by modulating the chemical activity/efflux propensity of GPLs