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Journal of Chromatography A, 1217 (2010) 4087–4099

Contents lists available at ScienceDirect

Journal of Chromatography A

journa l homepage: www.e lsev ier .com/ locate /chroma

omprehensive blood plasma lipidomics by liquid chromatography/quadrupoleime-of-flight mass spectrometry

oen Sandraa,b,∗, Alberto dos Santos Pereirab, Gerd Vanhoenackerb, Frank Davidb, Pat Sandraa,b

Metablys, Kennedypark 26, 8500 Kortrijk, BelgiumResearch Institute for Chromatography (RIC), Kennedypark 26, 8500 Kortrijk, Belgium

r t i c l e i n f o

rticle history:vailable online 24 February 2010

eywords:ipidomicsetabolomics

C–MS

a b s t r a c t

A lipidomics strategy, combining high resolution reversed-phase liquid chromatography (RPLC) with highresolution quadrupole time-of-flight mass spectrometry (QqTOF), is described. The method has carefullybeen assessed in both a qualitative and a quantitative fashion utilizing human blood plasma. The inherentlow technical variability associated with the lipidomics method allows to measure 65% of the featureswith an intensity RSD value below 10%. Blood plasma lipid spike-in experiments demonstrate that relativeconcentration differences smaller than 25% can readily be revealed by means of a t-test. Utilizing an

qTOFetstreamlood plasma

advanced identification strategy, it is shown that the detected features mainly originate from (lyso-)phospholipids, sphingolipids, mono-, di- and triacylglycerols and cholesterol esters. The high resolutionoffered by the up-front RPLC step further allows to discriminate various isomeric species associated withthe different lipid classes. The added value of utilizing a Jetstream electrospray ionization (ESI) sourceover a regular ESI source in lipidomics is for the first time demonstrated. In addition, the application ofultra high performance LC (UHPLC) up to 1200 bar to extend the peak capacity or increase productivity

is discussed.

. Introduction

A novel trend in life sciences lies in the global non-targeted anal-sis of biomolecules which has led to the disciplines of genomics,ranscriptomics, proteomics and metabolomics. Genomics has ini-iated this omics cascade and the concept of unbiased analysisubsequently attracted a vast amount of researchers to the omicseld. The potentials of these relatively new disciplines are indeednormous as they might impact on biomarker discovery, drug dis-overy/development and system knowledge [1–4], amongst others.

The realization that lipids not only serve as building materi-ls of membranes and energy providers but are also involved iniological processes such as signaling, cell–cell interactions, etc.nd, moreover, are linked to diseases such as diabetes, obesity,therosclerosis, Alzheimer, etc., has led to the emergence of theiscipline of lipidomics [4–9]. Lipidomics, often regarded as a sub-

et of metabolomics, aims at the comprehensive measurement ofhe lipids present in a cell, tissue, biological fluid, etc. and theoncomitant detection of the lipid responses to various stimuli,.g. disease and pharmaceutical treatment. This holistic approach,

∗ Corresponding author at: Metablys, Kennedypark 26, 8500 Kortrijk, Belgium.el.: +32 56204031.

E-mail addresses: koen.sandra@metablys.com (K. Sandra),at.sandra@richrom.com (P. Sandra).

021-9673/$ – see front matter © 2010 Elsevier B.V. All rights reserved.oi:10.1016/j.chroma.2010.02.039

© 2010 Elsevier B.V. All rights reserved.

simultaneously measuring hundreds of species, is revolutionarysince it allows to reveal differences between conditions withouta priori knowledge.

As part of our lipidomics platform, we recently describedthe analysis of the fatty acids in a single drop of human bloodusing capillary gas chromatography–mass spectrometry (GC–MS).A retention time locked database was constructed with morethan 100 fatty acids and related substances [10]. It is, however,of equal importance to study the intact lipids. The researcher isconfronted with a substantial complexity originating from an enor-mous structural diversity and dynamic range. Mass spectrometry,particularly using electrospray ionization (ESI), is the principalenabling technology to tackle the lipidome [9,11–14]. The com-plexity of the sample under investigation evidently benefits fromthe use of high resolution, accurate mass and tandem mass spec-trometric equipment. Therefore, FT-ICR, orbitrap and (Q)-TOF MSsystems are dominating the lipidomics literature [15–20]. Triplequadrupole instruments [21–23] have as well proven their valuefor the class-specific detection through precursor ion and neutralloss scanning. A number of researchers solely rely on mass spec-trometry to measure the lipidome and in the so-called shotgun

lipidomics approach intra-source separation is exploited to widenthe lipidome coverage [19,20,22,24]. Impressive results have beenreported but one is inevitably confronted with the fact that themass spectrometer can only tolerate a certain complexity, has alimited in-spectrum dynamic range and is sensitive towards ion

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uppression. This, combined with the knowledge that lipid struc-ures often come in a variety of isomers, which are difficult, if notmpossible, to distinguish solely relying on mass spectrometry, jus-ifies the combined use of chromatography and mass spectrometry.arious reports describe the combination of either reversed-phaser normal-phase HPLC with mass spectrometry and the combina-ion of both in multidimensional set-ups has been reported as well15–18,25–28]. It is obvious that, in recent years, the field of lipidnalysis has substantially been reshaped and revitalized largelyriven by advances in mass spectrometry and chromatography29]. Nevertheless, the field is in a continuous search/quest to fur-her mine the lipidome, in a comparative/quantitative fashion, withhe ultimate goal to widen our biological knowledge. Further con-ributing to this search, the present paper reports on a lipidomics

ethod, applied on human blood plasma, utilizing high resolutioneversed-phase liquid chromatography hyphenated to JetstreamSI-QqTOF mass spectrometry. To demonstrate the power, bothhe qualitative and quantitative aspect of the method are carefullyssessed.

. Experimental

.1. Reagents and materials

LC–MS grade water, methanol, ammonium formate, formic acidnd HPLC grade chloroform and isopropanol were purchased fromiosolve (Valkenswaard, The Netherlands). Phospholipid standardsere acquired from Larodan Fine Chemicals (Malmö, Sweden).uman blood EDTA plasma was obtained from healthy volunteers

hrough venipuncture.

.2. Sample preparation

Plasma lipids were extracted by adding 200 �L of ice-cold−20 ◦C) chloroform/methanol (1:2) to 10 �L of blood plasma.fter vortex-mixing, 200 �L of water was added followed by aecond round of vortex-mixing after which the mixture was cen-rifuged at 10,000 rpm for 10 min thereby generating a loweripophilic and upper hydrophilic phase separated by a protein layer.or the lipidomics measurements, 50 �L of the lower phase wasemoved and an equal amount of isopropanol was added prior tonjection. For the spike-in experiments, varying amounts of 1,2-di-leoyl-sn-glycero-3-phosphatidylcholine (PC18:1/18:1) and 1,2-i-oleoyl-sn-glycero-3-phosphatidylethanolamine (PE18:1/18:1)ere added to the plasma samples prior to extraction.

.3. Instrumentation

A 1200 or 1290 Infinity LC system (Agilent Technologies, Wald-ronn, Germany) was coupled to an Agilent 6530 QqTOF masspectrometer equipped with a Jetstream ESI source. The humanlood plasma lipid fractions were subjected to an XBridge BEH C18hield column (100 mm L × 2.1 mm ID × 1.7 �m dp – Waters, Mil-ord, MA, USA) kept at 80 ◦C in a Polaratherm 9000 series ovenSandraSelerity Technologies, Kortrijk, Belgium). Mobile phases,elivered at 0.5 mL/min, consisted of ammonium formate (20 mMt pH 5) (A) and methanol (B). The presence of species with a varyingegree of polarity required the application of a multi-step gradiento deconvolute the lipid species: 50–70% B in 14 min followed by alow gradient of 70–90% B in 50 min and an isocratic separation at0% B during 15 min. Mobile phase B subsequently reached 100% in

min where it was maintained for an additional 5 min. UHPLC mea-

urements were either performed at 1 mL/min (high productivity)n the 100 mm column or at 0.5 mL/min on a coupled column sys-em (2 × 100 mm) (high resolution). Time was adapted to maintainhe same gradient steepness thereby reducing the analysis time by

A 1217 (2010) 4087–4099

halve in the former case or doubling the analysis time in the lattercase.

A Jetstream ESI source, operated in positive and negative ioniza-tion mode, was applied for sensitive mass spectrometric detectionof the various lipid classes. Needle voltage was set at +/− 3.5 kV,nebulizer gas at 35 psig, drying and sheath gas flow rate and tem-perature at, respectively, 8 and 6 L/min and 300 ◦C. Apart from thesheath gas and temperature, which are not available, measure-ments performed using the regular ESI source utilized the samesource settings. UHPLC measurements performed at 1 mL/minrequired the fine tuning of the source parameters for efficientdesolvation (drying gas: 9 L/min, nebulizer gas: 45 psig, sheathgas: 7 L/min). The TOF was calibrated on a daily basis and sub-sequently operated at high accuracy (<5 ppm) without utilizingreference masses. Data were collected in centroid mode at a rate of1 spectrum per s in the extended dynamic range mode (2 GHz),utilizing two detector settings, offering a resolution of 9000 atm/z 622.0296. MS/MS experiments were performed in the data-dependent acquisition (DDA) mode. One survey MS measurement,was complemented with 3 data-dependent MS/MS measurementsresulting in a cycle time of 4 s. Only singly charged precursorions were selected based on abundance. After being fragmentedtwice, a particular m/z value was excluded for 30 s. Selecting thesame m/z value twice, increases the chance of measuring a par-ticular precursor at its maximum intensity while an exclusiontime of 30 s allows to obtain MS/MS information on chromato-graphically resolved isomers. The quadrupole was operated atmedium resolution and the collision energy was fixed at 15 eV. Alldata were acquired using MassHunter software (Agilent Technolo-gies).

2.4. Data analysis

Initial data processing, which involved feature extraction, wasdone using the MassHunter software. The feature extraction algo-rithm took all ions into account exceeding 1000 counts with acharge state equal to one and a feature had to be composed of twoor more ions to be valid (e.g. two ions in the isotope cluster). Isotopegrouping was based on the common organic molecules model. Inthe positive ionization mode, the algorithm searched for, and even-tually combined, protonated molecules and sodium, potassium andammonium adducts and placed the same weight on all of thesespecies (see later). Since lipids typically appear as one species innegative mode, adduct deconvolution was not utilized. The result-ing feature files were subsequently imported into Genespring MSor Mass Profiler Professional software (Agilent Technologies) whichaligned, normalized, visualized and filtered the features. In caseused, per run and per mass median normalization was applied.Statistical analyses were performed in Mass Profiler Professional.Molecular formulas were generated in the MassHunter softwareusing the Molecular Formula Generator algorithm. The algorithmtakes both mass accuracy and isotope information (abundance andspacing) into account to limit the number of hits and has a built-in logic to eliminate chemically implausible compositions. Onlythe common elements C, H, N, O, P and S were considered in thegeneration of formulas.

3. Results

For a method to be successfully implemented in lipidomic stud-

ies, it has to fulfill two major requirements. The method shouldbe designed to cover a substantial portion of the lipidome and itshould posses a technical variability that is much smaller than thebiological variability. The RPLC–ESI-QqTOF-MS method describedaddresses these requirements.

K. Sandra et al. / J. Chromatogr. A 1217 (2010) 4087–4099 4089

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ently as these species are detected in their [M−H]−, [M+HCOO]−,[M+Cl]− and [M+TFA]− state. Cholesterol esters, mono-, di- and tri-acylglycerols are observed as [M+NH4]+ ions again accompaniedwith traces of [M+Na]+ and [M+K]+ ions. In the 2D LC–MS map

Table 1Major lipid classes detected.

Lipid class Positive mode Negative mode Time/mass window

Lysophospholipids + + AMonoacylglycerols + − BPhospholipids + + C

ig. 1. LC–MS TIC (top) and base peak chromatogram (bottom) acquired in, respectipid extract was injected, in the latter case 5 �L. The TIC chromatogram obtained inholesterol esters and triacylglycerols elute. Marked elution windows (A–H) are in

.1. Qualitative aspect: insight into the blood plasma lipidomeoverage and LC–MS(/MS) behavior of the various lipid classes

The blood lipidome is composed of a complicated mix-ure containing cholesterol esters, phospholipids (e.g.lyso)phosphatidylcholine, (lyso)phosphatidylethanolamine),phingolipids (e.g. ceramide, sphingomyelin), mono-, di- andriacylglycerols, etc. which vary in fatty acid composition andlycerol backbone occupation [16,17,30]. The resulting largetructural diversity makes it challenging to develop a comprehen-ive method. The complexity of the sample under investigationvidently benefits from the use of high resolution chromatographyombined with high-end mass spectrometric equipment withnherent high resolution, accurate mass measurement and tandem

S capabilities. In the present work, a QqTOF MS system wasomplemented with an RPLC methodology utilizing small chro-atographic particles (1.7 �m), elevated temperature (80 ◦C) and

arefully designed elution conditions to maximize the inter- andntra-species resolution. The solvent system chosen is compatible

ith mass spectrometry and allows the ionization of a wide rangef lipids. At the temperature used, methanol appears to possessufficient eluting power to elute all lipid species without anyarry-over. A typical LC–MS total ion current (TIC) chromatogramf a blood plasma lipid extract obtained in positive ionizationode and a LC–MS base peak chromatogram acquired in negative

onization mode are shown in Fig. 1. To obtain a better view on theverall picture the corresponding 2D LC–MS plots are shown inig. 2. Instead of plotting the raw LC–MS data, the 2D map displayseatures, colored by abundance. A feature, in principle corre-ponding to a lipid, results from a feature extraction algorithmhat localizes and combines all related ions (including isotopes,dducts, dimers, charge variants) with the generation of a singleass (median), retention time (peak apex) and an abundance (sum

f all ions). The plot only displays the features that are consistentlyetected upon analyzing the same blood plasma extract threeimes (i.e. detected in 3 out of 3 runs). The plot therefore only

hows the data that matters. In comparative lipidomic studies,hese features are carefully assessed in different samples and up-r down-regulation is revealed by evaluating this pool of featuresy statistical tools, hence, it is important to filter out all irrelevantata.

positive and negative ionization mode. In the former case, 2 �L of the blood plasmative ionization mode gave serious ion suppression in the region where the neutralance with Table 1.

An enormous complexity is revealed, immediately illustratingthe power of the LC–MS methodology. In lipidomics studies it is notthe aim to identify all the detected compounds. In the present work,however, efforts were undertaken to identify a variety of com-pounds to get a better feeling with the data. The QqTOF system isvery powerful in that respect. The identification strategy consistedof the generation of molecular formulas based on accurate mass,isotopic abundance and spacing both in positive and negative ion-ization mode complemented with database searching in the LipidMaps (www.lipidmaps.org) and Human Metabolome Database[31] and MS/MS measurements in both modes. As will briefly bedemonstrated below, lipid elution behavior further assisted in theidentification. Table 1 displays the major classes detected and theirlocation in the chromatograms and 2D maps. A separation intodifferent lipid classes becomes apparent. In accordance with obser-vations reported in the literature [17,32–34], (lyso)phospholipidsand sphingolipids (sphingomyelin and ceramide) are detected inboth ionization modes, while cholesterol esters, mono-, di- andtriacylglycerols solely appear in the positive ionization mode. Phos-pholipids and sphingolipids are typically detected as [M+H]+ ions,with traces of [M+Na]+ and [M+K]+ ions. Phosphoinositol lipids rep-resent an exception. Ammonium adducts are prevalent for thislipid class. Phosphatidylcholines and sphingomyelins appear as[M+HCOO]− ions in negative mode while the other phospholipidsare detected in their deprotonated state. Ceramides behave differ-

Sphingomyelins + + DCeramides + + EDiacylglycerols + − FCholesterol esters + − GTriacylglycerols + − H

4090 K. Sandra et al. / J. Chromatogr.

Fig. 2. 2D LC–MS feature maps, colored by abundance, of the blood plasma lipidextract in positive (A) and negative (B) ionization mode. The plot displays the non-normalized, median intensity of the features detected in 3 out of 3 LC–MS replicates.Retention time/mass regions are marked in accordance with Table 1. The valuesassociated with the color bar on the right correspond to the ion counts. Ions withintensity values below 1000 were not considered by the feature extraction algo-rithm. Cholesterol esters give rise to intense in-source fragmentation ions at m/z3ea

ssuolbtd2wlbtstap[ewcs

and degree of unsaturation further becomes apparent upon con-

69.35, corresponding to dehydrated cholesterol. (For interpretation of the refer-nces to color in this figure legend, the reader is referred to the web version of therticle.)

hown in Fig. 2A, these co-variant ions are typically displayed as aingle feature. The plot reveals 1528 features consistently detectedpon analyzing the same blood extract three times (detected in 3ut of 3 runs). Considering features detected in 2 out of 3 analyseseads to a further increase to 2103. This increase will on one hande attributed to lipid species of lower abundance. Upon reducinghe ion count threshold (from 1000 to 500), the number of featuresetected in 3 out of 3 and in 2 out of 3 runs increased to 1777 and578, respectively. The features repeatedly detected in blank runsere only a negligible fraction of the features detected upon ana-

yzing the blood plasma lipid extracts, hence, most features coulde attributed to lipids. The way features are extracted is very impor-ant. The algorithm was set to put the same weight on protonatedpecies and salt adducts. This setting was chosen because choles-erol and mono-, di- and triacylglycerols are typically detecteds salt adducts while phospholipids and sphingomyelins appearredominantly in their protonated state. In this way, the [M+H]+,M+Na]+ and [M+K]+ ions associated with phosphatidylcholines, for

xample, and the [M+NH4]+, [M+Na]+ and [M+K]+ ions associatedith triacylglycerols are each merged into a single feature. Upon

hoosing the setting where protonated ions dominate, ammonium,odium and potassium adducts of triacylglycerol will be regarded

A 1217 (2010) 4087–4099

as unique features giving rise to an overestimation of the numberof unique lipids. Indeed, the number of features increases to 1861(100%, 2331 in 2/3) upon using this setting. Despite this, handlingthe different adducts as independent features can be valuable aswill be demonstrated below. All this is less of an issue in negativeionization mode where, apart from the ceramides, lipids typicallyappear as single species. The plot displayed in Fig. 2B reveals 955features detected in 3 out of 3 runs. A slight overestimation isexpected since the different ceramide adducts are considered asindependent features. Evidently, one has to realize that not a sin-gle feature extraction algorithm is flawless and merged and splitfeatures do occur. Isomers that are poorly resolved chromatograph-ically, can end-up in a single feature (see below).

Inter- and intra-species elution behavior can easily be explained[17,28,35] and the following paragraphs are devoted to a descrip-tion of this. At the same time, more insight into the various speciesdetected is provided.

3.1.1. (Lyso)phospholipids and sphingolipidsLyso- or monoacylphospholipids with one fatty acid attached

to the glycerol backbone elute earlier compared to diacylphospho-lipids due to the contribution of two fatty acids to the interactionwith the stationary phase. This phenomenon also explains theintra-species resolution. The more carbon atoms and the less dou-ble bonds, the more retention [35]. Fig. 3 illustrates this for anumber of phosphatidylcholines (PC) differing in the number ofdouble bonds (Fig. 3).

The figure also shows the ability of the method to resolve iso-meric compounds. MS/MS data, acquired in the data-dependentmode, confirmed that all these isomers are effectively associatedwith the same choline head group. Collision induced dissociationof protonated phosphatidylcholine lipids typically gives rise to anintense phosphorylcholine ion at m/z 184.07 [32,33]. The isomersobserved consequently vary in their fatty acid content or positionon the glycerol backbone, i.e. sn-1 or -2. To determine the fatty acidcontent, MS/MS was performed in the negative ionization mode.This typically allows to detect the liberated fatty acids [32,33]. Fig. 4displays the MS/MS spectra in both the positive and negative ion-ization mode acquired for the two PC36:2 isomers. Spectra wereacquired during 1 s and a lipid precursor was excluded for 30 s after2 MS/MS spectra were acquired. This exclusion time period allowedthe fragmentation of most isomers.

Fig. 4A, representing the MS/MS spectra of the two iso-mers acquired in the positive ionization mode, clearly shows thepresence of the phosphorylcholine ion at m/z 184.07. Fig. 4B, repre-senting the MS/MS spectra in the negative ionization mode, shows,apart from the loss of methyl formate (demethylation of the cholinehead group), fatty acid derived carboxylate anions which are veryillustrative for the structure under investigation. The spectrumassociated with the minor PC36:2 peak, displays an ion at m/z281.25 which corresponds to a mono-unsaturated octadecenoicacid (C18:1). This peak, hence, originates from a phosphatidyl-choline with the sn-1 and -2 positions occupied by a C18:1 fattyacid. The MS/MS spectrum associated with the larger peak con-tains carboxylate anions at m/z 279.23 and 283.26 correspondingto C18:2 and C18:0 fatty acids which are present at either the sn-1 orsn-2 position of the glycerol backbone. Determination of the actualfatty acyl group position on the glycerol backbone can be achievedby MS/MS upon consulting the carboxylate anion ratio [32], but israther difficult in real-life situations.

The correlation between retention time and carbon chain length

sulting the 2D LC–MS feature plot (positive ionization mode)zooming in on the lysophospholipids (Fig. 5).

This correlation further assists in the identification process. Byway of example, consider the feature labeled LPC17:1. This feature

K. Sandra et al. / J. Chromatogr. A 1217 (2010) 4087–4099 4091

Fig. 3. Extracted ion chromatograms (EIC) in the positive ionization mode of a number of phosphatidylcholines (PC) differing in the number of double bonds. Ions weree elimr labelew be elut

iahci

Fl

xtracted at 5 ppm mass accuracy (from the exact lipid mass) which is sufficient toevealed by performing MS/MS (see Fig. 4), is reported on top of the peaks. The peakith the more abundant PC36:4, and its fatty acid composition could therefore not

han species solely containing unsaturated species.

s just intense enough to be recognized by the feature extraction

lgorithm. The molecular formula, C25H50NO7P, generated withigh confidence by the molecular formula generation algorithm,an be linked to a LysoPE20:1 or LysoPC17:1 structure. MS/MSnformation was not retrieved in the data-dependent mode and

ig. 4. MS/MS measurements performed on the minor and major PC36:2 isomers (Fig. 3)abeled.

inate the isotopes associated with other PC species. The fatty acid composition, asd with the asterisk did not result in a clean MS/MS spectrum, due to the co-elution

cidated. Remarkably, species containing one saturated fatty acid always elute later

the peak was not observed in the negative ionization mode, hence,

it could not be determined whether a formate adduct exists, whichwould confirm the presence of a choline head group. The positionin the plot helps to positively identify this species as LysoPC17:1.LysoPE20:1 is expected to elute around 17 min given its elution

in positive [M+H]+ (A) and negative [M+HCOO]− (B) ionization mode. Precursor is

4092 K. Sandra et al. / J. Chromatogr.

Fig. 5. 2D LC–MS feature map in the positive ionization mode displaying thelysophospholipids (LPC: lysophosphatidylcholine, LPE: lysophosphoethanolamine).Lysophosphatidylcholines with the same carbon chain length and the same degreeof unsaturation are connected, illustrating the correlation between elution and num-brt

cbcgcaaLmtst

rw[

PE36:2 ([M+H]+: 744.553772) nearly co-elutes with PC18:1/P-16:0

Fr

er of carbons and double bond. The plot displays the features detected in 3 out of 3eplicates. LPE16:0 and others could be revealed upon consulting the plot displayinghe features that were only detected in 2 out of 3 runs.

orrelation with PC with the same fatty acid composition (seeelow). Again isomeric species are revealed in the plot whichan be attributed to the occupation of different positions on thelycerol backbone since MS/MS experiments learn that the samearboxylate anions are generated. From the plot it further becomespparent that plasmanyl phospholipids, with the aliphatic chainttached to the glycerol backbone via a alkyl ether linkage (e.g.PC(O-18:0)), are more retentive than their plasmalogen (plas-enyl phospholipid) counterparts (e.g. LPC(P-18:0)) which have

he aliphatic chain attached through a vinyl ether linkage. Thesepecies are as well observed, combined with a fatty acyl linkage, inhe region of the phospholipids.

Considering the different phospholipid classes, intra-speciesesolution is readily obtained. This is in contrast to normal-phase LChich typically resolves phospholipids based on their head group

27]. In case of the choline and ethanolamine head group, it is clear

ig. 6. Extracted ion chromatograms in the positive ionization mode of PC36:2 and PE3evealed.

A 1217 (2010) 4087–4099

that the separation based on fatty acid content is more prevalentthan the separation based on the head group [35]. Fig. 6 illustratesthis. PC18:1/18:1 and PE18:1/18:1 nearly co-elute, while thesespecies are resolved from their corresponding 18:0/18:2 isomers.

Despite the different head group, i.e. choline vs. ethanolamine,PC36:2 and PE36:2 nearly elute at the same retention time. Thedifference in abundance does not reflect the true situation in bloodsince PE species have a lower ionization efficiency in positive modecompared to PC species [33]. Using standard lipids with identi-cal fatty acid content (PC18:1/18:1 and PE18:1/18:1), we deducedthat, for the same concentration injected, the detectability of the PEspecies in positive ionization mode is typically less than 10% of thedetectability of the corresponding PC species. In negative mode,ionization efficiency increases to 65% of that of the PC species.As a result, PE species become much more apparent in negativeionization mode and this justifies the combination of the two ion-ization modes in lipidomics. The same phenomenon holds truefor the other phospholipid classes, i.e. improved detectability innegative ionization mode. Fig. 6 also shows the existence of a phos-phatidylcholine lipid (PC33:2) with the same exact mass as thephosphatidylethanolamine lipid (PE36:2). This further illustratesthe importance of the ability to perform MS/MS to discriminatethese two species. In addition, measurements in negative modealso discriminate between PC and PE since the former are detectedas formate adducts while the latter appear as deprotonated species.PE36:2 also gives rise to two chromatographically resolved isomersdiffering in their fatty acid content. The first isomer corresponds toa phosphatidylethanolamine with the sn-1 and -2 positions occu-pied by a C18:1 fatty acid. The second, more intense, isomer canbe attributed to a phosphatidylethanolamine with the sn-1 and -2positions occupied by a C18:2 and a C18:0 fatty acid. It appears thatPE36:2 and PC36:2 are very identical in their fatty acid organization,including the intensity of the isomers. It is interesting to briefly dis-cuss the path that led to this identification (consult supplementaryFigure S1). The MS/MS spectrum in positive ionization mode gaverise to a spectrum with a neutral loss of 141.05 amu, correspond-ing to phosphorylethanolamine, accompanied with an intenseion at m/z 184.07 indicative for a PC structure [32,33]. Indeed,

([M+H]+: 744.590149) only differing 0.0364 Da in mass. Duringthe precursor selection, quadrupole resolution was insufficient toresolve these two structures, hence, both end-up in the collisioncell explaining the mixed MS/MS spectrum. Structure specific spec-

6:2. Ions were extracted at 5 ppm mass accuracy. An isobaric PC33:2 structure is

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K. Sandra et al. / J. Chroma

ra could, however, be obtained in negative ionization mode dueo the appearance of the PC as a formate adduct. PC18:1/P-16:0ould be identified in negative ionization mode due to the forma-ion of a carboxylate anion with m/z 281.25 corresponding to C18:1.he plasmalogen itself does not gives rise to a detectable fragmentut the identification of the fatty acyl part allows the plasmalo-en to be identified as P-16:0. Interesting to note is that an isomerlutes several min earlier which can be attributed to PC16:1/P-8:0. Phosphatidylinositol and -serine lipids, which are present atuch lower abundance in blood [30], elute earlier than their phos-

hatidylcholine and -ethanolamine counterparts. Another eventhat renders lipids more hydrophilic is oxidation of the fatty acids.his is demonstrated in supplementary Figure S2. The ability toetect oxidized phospholipids is important since these species arenown to play important biological roles [36].

Sphingomyelins are abundantly detected and elute in the regionf the phospholipids, which is not surprising considering the struc-ural similarity. Isomeric species are revealed as well which cane attributed to variations in the sphingoid base (e.g. sphinga-ine and sphingosine) combined with fatty acid compensations.his is, however, difficult to deduce from the MS/MS spectra sinceragmentation of the sphingomyelin lipids only gives rise to thehosphorylcholine ion at m/z 184.07 in positive ionization modend to the loss of methyl formate from the precursor in negativeonization mode. In no case, was a carboxylate ion observed which

s in contrast to the phosphatidylcholine lipids. Ceramides eluteater than their sphingomyelin counterparts due to the absence ofhe phosphatidylcholine head group. The MS/MS spectra obtainedn the [M+H]+ and [M−H]− ions are very informative [34,37,38].nformation on the long chain base moiety can be obtained in both

ig. 7. (A) Extracted ion chromatogram in the positive ionization mode of DAG36:2. Ionshe DAG36:2 isomers in positive ionization mode [M+NH4]+. The inset shows a more deta

1217 (2010) 4087–4099 4093

positive and negative ionization mode, while fragment ions con-taining the acyl moiety are solely present in the negative ionizationmode. The adducts (TFA, chloride, formate), on the other hand, donot give rise to relevant fragment ions.

3.1.2. Cholesterol esters, mono-, di- and triacylglycerolsCholesterol esters and triacylglycerols, the more apolar species,

are very retentive on the column used. Cholesterol esters only bearone fatty acid moiety but the head group, namely cholesterol, sub-stantially contributes to the retention. The diacylglycerols with twofatty acids attached to the glycerol backbone elute earlier comparedto the triacylglycerols due to the contribution of three fatty acids tothe interaction with the stationary phase in the latter case. The res-olution between the different triacylglycerol species is achieved inthe isocratic part at 90% MeOH. This explains the slightly broaderpeaks in comparison to the other classes. Mono- and diacylglyc-erol intra-species resolution was not specifically tuned since theyelute in the region of the phospholipids. Mono-, di- and triacyl-glycerols give rise to isomeric species and MS/MS experimentsprovide insight into the fatty acid composition. The same frag-mentation rules apply for all these species. Performing MS/MS onthe [M+NH4]+ ions gives rise to a neutral loss of the fatty acids[17,28]. This is illustrated in Fig. 7 for DAG36:2. Two isomers areclearly visible in the extracted ion chromatograms (Fig. 7A) andMS/MS experiments performed on the fly in the data-dependent

acquisition mode generated valuable spectra corresponding to eachisomer (Fig. 7B). The resolution between the isomers was suffi-cient to allow the DDA algorithm to select the same m/z value fora next round of MS/MS (exclusion time: 30 s). Upon consulting theMS/MS spectra, it is obvious that a difference in the occupation on

were extracted at 5 ppm mass accuracy. (B) MS/MS measurements performed oniled view on the neutral fatty acid loss associated with the minor DAG36:2 species.

4094K

.Sandraet

al./J.Chromatogr.A

1217 (2010) 4087–4099Table 2Technical variability described in terms of EIC area RSD, feature intensity RSD, and retention time RSD measured on a substantial number of lipids of different classes, present at higher and lower abundance. The table also reportsthe intensity gain upon using the Jetstream ESI source compared to the regular ESI source.

Lipid Extraction triplicate LC–MS triplicate Jetstreamenhancementa

EIC area Featureintensityb

Retention time (min) EIC area Featureintensityb

Extract 1 Extract 2 Extract 3 % RSD % RSD Extract 1 Extract 2 Extract 3 % RSD LC–MS1 LC–MS2 LC–MS3 % RSD % RSD

LysoPC 16:0 1217437 1392557 1261645 5.76 <10% 11,894 11,888 11,913 0.09 1261645 1250889 1269173 0.60 <5% 3.95LysoPC 16:0 11205799 12711129 11697734 5.28 <5% 12,690 12,688 12,714 0.09 11697734 11674644 11683257 0.08 <5% 3.76LysoPC 18:2 668488 695367 673028 1.73 <5% 10,659 10,650 10,671 0.08 673028 695271 657265 2.31 <5% 4.10LysoPC 18:2 5650560 6291707 5886584 4.46 <5% 11,418 11,410 11,435 0.09 5886584 5837870 5907071 0.49 <5% 4.03LysoPC 18:2 86285 123628 136164 18.37 <10% 12,060 12,070 12,100 0.14 136164 180748 150252 11.95 <5% ESI (−), JS (+)LysoPE 16:0 8530 11634 8314 15.98 <30% 12,839 12,851 12,867 0.09 8314 9216 9367 5.19 2 out of 3 3.26LysoPE 18:2 37791 41705 34198 8.09 <10% 11,577 11,571 11,607 0.14 34198 38338 36855 4.70 <5% ESI (−), JS (+)PC 16:0/P-18:0 3550425 3586372 3670814 1.40 <5% 46,457 46,454 46,453 0.00 3670814 3667748 3691895 0.29 <5% 3.40PC 16:1/P-18:0 3972056 4003710 4102082 1.38 <5% 43,562 43,578 43,579 0.02 4102082 4081201 4065992 0.36 <5% 3.21PC 18:1/P-16:0 2048068 2094978 2149560 1.98 <20% 45,952 45,958 45,960 0.01 2149560 2125930 2120525 0.59 <20% 3.39PC 33:2 1285538 1294954 1342052 1.89 <5% 38,193 38,225 38,227 0.04 1342052 1344070 1341097 0.09 <5% 3.43PC 34:1 126755447 126724582 130044322 1.22 <5% 43,567 43,584 43,583 0.02 130044322 129536937 129510559 0.19 <5% 2.54PC 34:1 OH 249173 251254 246373 0.80 <5% 38,264 38,288 38,293 0.03 246373 254859 255822 1.68 <5% 3.22PC 34:2 4484048 4486470 4641103 1.62 NFc 40,088 40,114 40,118 0.03 4641103 4594949 4619376 0.41 NFc 3.56PC 34:2 165301756 165755713 168619598 0.88 <5% 40,569 40,593 40,594 0.03 168619598 168634770 168766619 0.04 <5% 2.18PC 34:2 8451263 8525630 8818668 1.84 NFc 41,311 41,329 41,331 0.02 8818668 8674080 8821624 0.79 NFc 3.48PC 36:0 129692 121462 126405 2.69 <5% 51,315 51,338 51,323 0.02 126405 120624 123896 1.91 <10% 3.21PC 36:1 36314942 36391340 37676519 1.70 <5% 48,146 48,157 48,151 0.01 37676519 37292847 37194369 0.56 <5% 3.00PC 36:2 15391559 15414244 15929380 1.59 <10% 44,739 44,748 44,753 0.01 15929380 15688467 15730716 0.67 <10% 3.32PC 36:2 139116047 139407216 142701789 1.16 <5% 45,322 45,326 45,330 0.01 142701789 141927755 142237922 0.22 <5% 2.34PC 36:3 34947513 35028833 36143856 1.54 <5% 41,779 41,794 41,796 0.02 36143856 35948499 35954318 0.25 <5% 3.12PC 36:3 46880912 47247476 48651669 1.60 <5% 42,501 42,521 42,518 0.02 48651669 48366660 48251702 0.35 <5% 3.12PC 36:4 10177239 10171147 10522480 1.60 <5% 38,782 38,813 38,818 0.04 10522480 10433067 10509102 0.38 <5% 3.29PC 36:4 69377898 69625683 71254298 1.19 <5% 40,662 40,684 40,685 0.03 71254298 71044682 71110693 0.12 <5% 2.57PC 36:4 6899023 6970576 7119731 1.31 2 out of 3 43,567 43,584 43,583 0.02 7119731 7204471 7198309 0.54 2 out of 3 4.65PC 36:5 395636 394989 411123 1.86 <5% 36,150 36,162 36,170 0.02 411123 405813 405646 0.62 <5% 3.27PC 36:5 1092806 1097583 1128727 1.44 <5% 37,071 37,104 37,097 0.04 1128727 1130582 1138601 0.38 <5% 3.44PC 36:5 6953795 7014258 7240528 1.75 <5% 38,146 38,175 38,179 0.04 7240528 7185518 7239498 0.36 <5% 3.56PC 36:5 9199170 9288186 9469036 1.20 NF 40,559 40,584 40,582 0.03 9469036 9414644 9504655 0.39 NF 4.13PE 20:5/P-18:0 386090 392621 403590 1.83 <5% 44,483 44,449 44,489 0.04 403590 395725 391873 1.23 <5% 2.41PE 36:2 42357 17687 19152 42.81 <10% 45,015 45,051 44,996 0.05 19152 24002 20789 9.45 2 out of 3 3.24PE 36:2 216562 221084 223826 1.36 NFd 45,612 45,613 45,618 0.01 223826 195135 223007 6.23 NFd 2.47PI 38:4 40893 47280 51406 9.30 NF 40,119 40,132 40,113 0.02 51406 50579 50579 0.77 NF 3.00SM 20:0 5328562 5365550 5498722 1.35 <5% 46,586 46,585 46,583 0.00 5498722 5415155 5432423 0.66 <5% 3.18SM 22:0 12437841 12483694 12790679 1.25 <5% 50,836 50,841 50,841 0.00 12790679 12710320 12715916 0.29 <5% 3.06SM 23:1 1371534 1369759 1415923 1.54 <5% 49,376 49,388 49,386 0.01 1415923 1398183 1397148 0.61 <5% 3.04SM 23:1 1914585 1935149 1932471 0.47 <5% 50,019 50,026 50,027 0.01 1932471 1964788 1974405 0.92 <5% 3.08SM 24:1 23723754 23692666 24384406 1.33 <5% 51,362 51,367 51,366 0.00 24384406 24191300 24148048 0.42 <5% 2.96SM 24:1 5569447 5563448 5768472 1.69 <10% 52,054 52,057 52,051 0.00 5768472 5707112 5778160 0.55 <10% 3.15CE 18:2 172579008 175591792 177251336 1.10 <5% 67,740 67,730 67,717 0.01 177251336 174936425 176198341 0.54 <5% 1.53CE 18:3 14770791 15032035 15543177 2.12 <5% 65,879 65,867 65,861 0.01 15543177 15525573 15519555 0.06 <5% 2.68CE 18:4 145182 152468 150943 2.10 <5% 63,959 63,960 63,956 0.00 150943 153420 159334 2.28 <5% 3.00CE 20:3 6257715 6369313 6635507 2.47 <5% 68,783 68,777 68,762 0.01 6635507 6630960 6697191 0.45 <5% 2.88CE 20:5 3946484 4027209 4129085 1.85 <5% 65,403 65,391 65,387 0.01 4129085 4126497 4148634 0.24 <5% 3.01DAG 34:1 181441 178544 183076 1.04 <5% 49,986 50,002 49,991 0.01 183076 184544 181548 0.67 <5% 2.76DAG 34:1 78180 75273 78616 1.92 <40% 50,401 50,396 50,389 0.01 78616 76738 78912 1.23 <40% 3.17DAG 36:2 553836 551517 574739 1.86 <40% 51,057 51,059 51,052 0.01 574739 569765 574536 0.40 <40% 2.84DAG 36:2 211405 199963 207794 2.31 <5% 51,462 51,459 51,453 0.01 207794 208150 204165 0.87 <40% 2.88TAG 50:1 16272554 16373367 16754447 1.26 <5% 77,051 77,018 77,022 0.02 16754447 16701988 16708897 0.14 <5% 2.83TAG 52:3 108963497 109342142 112354894 1.38 <5% 75,053 75,026 75,033 0.02 112354894 111604410 112033726 0.27 <5% 2.24TAG 54:2 6767352 6771038 6957123 1.30 <5% 83,862 83,836 83,847 0.01 6957123 6950201 6990964 0.26 <5% 2.38TAG 54:3 40490725 40566554 41643242 1.29 <5% 79,515 79,488 79,486 0.02 41643242 41386095 41448271 0.26 <5% 2.62TAG 54:4 38299708 38514160 39655822 1.53 <5% 76,133 76,101 76,105 0.02 39655822 39390579 39560536 0.28 <5% 2.64TAG 54:5 18538357 18519129 19037503 1.28 <80% 73,304 73,279 73,281 0.02 19037503 19048660 19093638 0.13 <10% 2.90TAG 54:5 3713728 3760133 3804544 0.99 <5% 74,902 74,874 74,879 0.02 3804544 3871584 3857133 0.75 <5% 2.77a ESI (−) means not detected by regular ESI. JS (+) means detected by Jetstream ESI.b NF: not found; 2 out of 3 means that the compound was only detected in 2 out of 3 runs.c Features merged with the abundant main peak.d PE36:2 feature merged with PC16:0/P-16:0 which only differs 0.03 Da (see Supplementary Figure S1).

K. Sandra et al. / J. Chromatogr. A 1217 (2010) 4087–4099 4095

Table 3Features detected in both positive and negative ionization mode at different intensity precision levels (% RSD) both for the LC–MS triplicate and extraction triplicate (positiveand negative ionization mode). Unless noted, precision is reported for normalized features.

All features Features in 2/3 Features in 3/3 RSD <30% RSD <20% RSD <10% RSD <5%

LC–MS triplicate (+) mode 3418 2103 1528 1418 1322 1086 748LC–MS triplicate (+) mode (no normalization) 3418 2103 1528 1419 1328 1101 796

ass va

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3

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a

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Extraction triplicate (+) mode 3528 2091Extraction triplicate (−) modea 1604 1153

a Not to overestimate the number of features, some late eluting peaks with high m

he glycerol backbone partially explains the existence of the twosomers. An intense peak resulting from the neutral loss of C18:1llustrates that two positions are occupied with an octadecenoiccid. The smaller peak further hides another unresolved minor iso-er bearing one C18:0 and one C18:2 fatty acid on the glycerol

ackbone. Additional MS/MS data on TAG isomers can be found inupplementary Figure S3.

.1.3. OthersApart from the above-described lipids a substantial number

f other lipophilic species (identified and unidentified) can beetected in both ionization modes. By way of example, ubiquinone10 and alpha-tocopherol were identified based on their molecu-

ar formulas generated using the MFG algorithm and their MS/MSpectra acquired in the data-dependent mode. Ubiquinone Q10ppears as an ammonium adduct while alpha-tocopherol appearss a protonated species. The MS/MS spectra of alpha-tocopherolnd ubiquinone Q10, supplemented as Figure S4, show some veryharacteristic ions [39,40]. The quinone-derived ion at m/z 197.08,or example, dominates the spectrum of ubiquinone Q10 [40]. Inddition, a more subtle ladder of ions, being informative for theliphatic chain, is observed.

It is obvious that the method covers a substantial portion of theipidome but the question that evidently arises is whether theseipids are measured in a quantitative fashion. The next paragraphighlights the quantitative aspect of the methodology.

.2. Quantitative aspect: technical variability and discriminatingower

The final goal of any lipidomics or metabolomics method is topply it to address a biological question, this by revealing lipid oretabolite up- or down-regulation in comparative experiments.direct consequence is that the technical variability should be as

mall as possible to highlight subtle biological differences. Table 2,

isplays the relative standard deviation (RSD %) on the area for aange of lipids upon performing a triplicate LC–MS measurementpositive ionization mode) of the same blood plasma lipid extractLC–MS repeatability) or upon analyzing the same blood plasmaample extracted in triplicate (extraction repeatability). Upon com-

able 4pike-in experiment.

Condition PC(18:1/18:1)

Amount spiked in blood plasma (ng) Final conc. (ng/10 �L plasm

0 0 117a

1 100 217 (1.85c)2 125 242 (1.12c)3 150 267 (1.10c)4 – –

a PC concentration revealed based upon the equation retrieved by plotting the feature iddition approach.b This compound was detected in the sample used for qualitative purposes (see Fig. 6

urposes. In both cases plasma of the same subject was used but taken at a different timec Theoretical fold change compared to previous condition. E.g. PC(18:1/18:1) concentrat

s given in Fig. 9.

1463 1284 1201 973 654955 892 840 610 288

lues (>80 min, >900 Da), which probably do not originate from lipids, were excluded.

paring the LC–MS and extraction repeatability, it becomes clear thatthe extraction evidently increases the technical variability but areaRSD values are still more than satisfactory. Apart for some out-liers, RSD values are typically below 5%. These outliers result fromintegration difficulties due to peak distortion because of the partialco-elution of lipids with similar masses. For illustrative purposes,the LC–MS TIC chromatograms associated with the analysis of theblood plasma extraction triplicate are shown in supplementaryFigure S5.

The reported areas were obtained by integrating the extractedion chromatograms (EIC). In an unbiased approach, this is not acommon way of working. Instead, features are extracted and com-parative experiments are based on feature intensity. It is thereforeimportant to utilize a robust feature extraction algorithm that isable to maintain the area RSD values reported in Table 2. Of equalimportance is to minimize retention time drift and mass deviationso that identical features/lipids in different samples/runs are cor-rectly aligned. Lipids are detected within 5 ppm in the differentruns without utilizing mass correction through the simultaneousinfusion of reference masses. Retention time RSD values, as well asthe feature intensity RSD values, are presented in Table 2. Reten-tion time repeatability is more than satisfactory. Upon consultingthe table it becomes clear that, in most cases, feature extractionis successful. In cases where feature intensity RSD values devi-ate substantially from the area RSD derived from the extractedion chromatograms, incomplete adduct deconvolution is typicallyobserved. By way of example, DAG36:2 is measured in the LC–MSand extraction triplicate with high precision based on the EIC area.The feature extraction algorithm, however, gives rise to a RSDvalue between 30 and 40% for the same lipid (two isomers). Acloser evaluation learns that, in one sample, the NH4 adduct isnot merged with the Na and K adduct while in the other twosamples the DAG36:2 feature is correctly composed of the ammo-nium, sodium and potassium adduct. This evidently leads to anunderestimation of the feature intensity immediately explaining

the low precision. In that respect, it is valuable, for quantitativepurposes, to use feature extraction settings which handles everyadduct as a distinct feature. Indeed, upon doing this, three DAG36:2features can be discriminated all measured with high precision(<5% RSD).

PE(18:1/18:1)

a) Amount spiked in blood plasma (ng) Final conc. (ng/10 �L plasma)

0 0b

10 1012.5 12.5 (1.25c)15 15 (1.25c)20 20 (1.25c)

ntensity in function of spike-in concentration (0, 100, 125 and 150 ng), i.e. standard

) but appeared to be below the limit of detection in the sample for quantitativeinterval (samples related to a time course study).

ion is 1.85 times higher in condition 1 vs. 0. Experimentally determined fold change

4096 K. Sandra et al. / J. Chromatogr.

Ffa

aisR

ttwcbtrafscictbbolctn

Faf

ig. 8. Discriminating power of the methodology visualized. All concentration dif-erences as reported in Table 4 can be extracted out of the complex data matrix usingt-test.

A more global view on the number of features measured withprecision below 5, 10, 20 and 30% in both positive and negative

onization mode is presented in Table 3. Supplementary Figure S6hows the 2D LC–MS feature maps associated with the differentSD values.

As stated above, the smaller the technical variability, the smallerhe differences in lipid concentration that can be revealed. To checkhis statement, two phospholipids (PE18:1/18:1 and PC18:1/18:1)ere spiked into the same blood plasma sample at different con-

entrations (Table 4) and subjected to the lipidomics strategy inoth positive and negative ionization mode. Every sample wasreated in triplicate and samples were randomized at sample prepa-ation and LC–MS level. After feature extraction, retention timend mass alignment, normalization and filtering, a t-test was per-ormed to extract these spiked compounds out of the matrix. Fig. 8hows the discriminating power of the methodology. All conditionsan be discriminated from one another in both ionization modesllustrating that large as well as small concentration differencesan be revealed. Indeed, differences in phospholipid concentra-ion as small as 25% can easily be discriminated with p-values wellelow <0.01 and concentration differences of only 10% can evene highlighted. This is a direct consequence of the high precision

f the methodology and illustrates the utility to address real bio-ogical questions. Fig. 9 shows the average read-out of the spikedompounds, following data processing, in function of the condi-ion (or concentration). For illustrative purposes, the read-out ofon-spiked closely eluting isomeric compounds is shown as well

ig. 9. Actual read-out of the spiked phospholipid species and non-spiked closely elutingnd PE18:1/18:1 read-out as obtained in negative ionization mode. Experimentally determold change value).

A 1217 (2010) 4087–4099

(corresponding to the PC and PE18:0/18:2 species presented inFig. 6).

It is interesting to briefly post a word on normalization. In typi-cal lipidomics experiments, comparing various biological samples,normalization is a critical and complex part and usually involvesthe addition of an array of standard compounds [16,41]. The presentmethodological paper utilizing the same blood plasma sample doesnot really benefit from normalizing the data using internal stan-dards since the only variation that occurs is technical by nature. Tocorrect for this technical variability, normalization in a global fash-ion, based on mean feature intensity, is justified. Nevertheless, asillustrated in Table 3, the high inherent precision of the method inprinciple allows to omit this normalization.

3.3. Jetstream ESI vs. regular ESI

The mass spectrometer has a serious impact on the outcomeof the experiments. A wide range of instruments, differing in per-formance, are on the market. In the so-called unbiased type ofanalyses evidently including lipidomics, resolution and sensitiv-ity are key. The resolution and sensitivity provided by the QqTOF,substantially contributes to an extended lipidome coverage. Apartfrom the mass analyzer, the ionization process is as important. Theprocess of electrospray is a widely adapted and proven technologyto present gas-phase ions to the mass spectrometer. The process,however, should be regarded as inefficient since the majority ofanalytes do not enter the mass spectrometer (due to ionizationand desolvation difficulties) and, hence, remain undetected. Theabove-described LC–MS methodology uses a specialized ESI sourceequipped with thermal gradient focusing technology which usessuperheated nitrogen to improve ion generation and desolvation.The technology greatly contributes to widening the lipidome cover-age. Table 2 compares the measured areas of several lipids utilizingthe classical ESI and the Jetstream ESI source. For all lipid classes, asubstantial intensity increase (up to a factor 4) is observed. Thelowest gain can often be attributed to species that saturate thedetector. One point of concern is evidently the in-source fragmen-tation that might arise due to the use of superheated nitrogen.

To assess this, the areas of some in-source fragments were com-pared and correlated to the increase in lipid detectability. Someintense cholesterol esters and triacylglycerol species were selectedand their most intense fragment ions, as observed upon performingMS/MS, were retrieved in the MS run. In the case of the cholesterol

isomeric compounds. PC18:1/18:1 read-out as obtained in positive ionization modeined fold change (FC) is reported as well (compare with Table 4 for the theoretical

togr. A

eBidTtcmi

Fi

K. Sandra et al. / J. Chroma

sters, the intensity of the dehydrated cholesterol ion was assessed.y way of example, using the Jetstream ESI source, the detectabil-

ty of CE20:5 is increased with a factor 3, the detectability of theehydrated cholesterol fragment ion is increased with a factor 2.7.his illustrates that the increased sensitivity for this ion is due to

he Jetstream process and not to in-source fragmentation. In thease of the TAG species, in-source fragmentation was assessed byeasuring the neutral loss of fatty acids. For these species, a slight

ncrease in in-source fragmentation was observed. By way of exam-

ig. 10. The impact of UHPLC on the resolution of some lipid isomers. Displayed are the en resolving power is clearly visible upon doubling the column length.

1217 (2010) 4087–4099 4097

ple, intact TAG54:4 increased with a factor 2.6, the detectability ofthe fragments corresponding to the neutral loss of C18:1 and C18:2increased with a factor 3. Very similar values were observed forother TAG species. Despite the fact that highly abundant triacyl-glycerols are evaluated, the abundances of these fragments do not

pass the feature extraction threshold and should therefore be con-sidered as very low abundant. Another path that leads to a moreefficient electrospray process is nanospray [17,19,20]. The addedvalue of nanospray in lipidomics will be assessed in our future work.

xtracted ion chromatograms of LysoPC18:2 (A), PC36:3 (B) and DAG36:2 (C). A gain

4098 K. Sandra et al. / J. Chromatogr. A 1217 (2010) 4087–4099

(Cont

3

ut1tttttpttanaotfaactiaiioiii

4

d

[

[

Fig. 10.

.4. UHPLC—productivity and resolution

The configuration described thus far, utilized a 100 mm col-mn packed with 1.7 �m particles operated at 500 bar. Switchingo a UHPLC system with extended pressure capabilities (up to200 bar) allows to either reduce the analysis time by increasinghe flow rate or increase the column length to further improvehe resolution. Both approaches were evaluated and compared tohe previously described methodology. To allow a fair comparison,he latter method utilizing the 100 mm column was transferredo the UHPLC system as well. In this way all instrument relatedarameters were excluded. Fig. 10 shows the impact of UHPLC onhe separation of isomeric species. It immediately becomes clearhat doubling the column length and analysis time does result insignificant gain in resolution. Some previously hidden isomers

ow become visible. In addition, resolution improvements lead toreduction in feature merging. Indeed, PE36:2 and PC18:1/P-16:0,nly differing 0.0364 Da in mass, appear as a merged feature usinghe standard method (see Table 2) but result in two independenteatures using the extended column length method. Alternatively,n increase in the resolution of the TOF might be envisioned, tocertain extent, to prevent this feature merging. Increasing the

olumn length, is a particularly popular approach in the field of pro-eomics and leads to an increased number of peptide and proteindentifications [42,43]. Considering the improved lipid resolution,similar explosion in identifications is expected and assessing this

s the subject of our present research. Increasing the productivitys yet another feature offered by UHPLC. Doubling the flow ratever the 100 mm column packed with 1.7 �m particles and reduc-ng the analysis time by halve, to maintain the gradient steepness,ncreased the pressure up to 1000 bar and resulted in ca. 20% lossn features.

. Conclusion

A powerful RPLC–ESI-QqTOF-MS lipidomics methodology isescribed and carefully assessed in terms of lipidome coverage,

[

[[

inued).

technical variability and discriminating power. All major lipidclasses are covered and the individual species, including isomers,are detected with high precision. The method, which is not lim-ited to blood plasma but can be applied to other biological fluidsand samples, is currently applied to address a variety of biologicalquestions.

Acknowledgements

The authors acknowledge Steve Fischer (Agilent Technologies,Santa Clara, CA) for his valuable input. This research is partiallyfunded by the Flemish agency for Innovation by Science and Tech-nology (IWT).

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.chroma.2010.02.039.

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