Rapid and Reliable Identification of Phospholipids ... - ACS Publications

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Rapid and reliable identification of phospholipids for untargeted metabolomics with LC-ESI-QTOF-MS/MS Joanna Godzien, Michal Ciborowski, María P. MartínezAlcázar, Paulina Samczuk, Adam Kretowski, and Coral Barbas J. Proteome Res., Just Accepted Manuscript • Publication Date (Web): 17 Jun 2015 Downloaded from http://pubs.acs.org on June 18, 2015

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Rapid and reliable identification of phospholipids for untargeted metabolomics with LC-ESI-QTOF-MS/MS Joanna Godzien1, Michal Ciborowski2, Maria Paz Martinez-Alcazar1, Paulina Samczuk2, Adam Kretowski2, Coral Barbas1*

1) CEMBIO, Centre for Metabolomics and Bioanalysis, San Pablo CEU University, Spain 2) Clinical Research Centre, Medical University of Bialystok, Pola

* To whom correspondence should be addressed: Coral Barbas, Pharmacy Faculty, Campus Monteprincipe, San Pablo-CEU University, 28668 Boadilla del Monte, Madrid, Spain, tel: 0034913724711, fax: 0034913724712, e-mail: [email protected]

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ABSTRACT Lipids are important components of biological systems, and their role can be currently investigated

by

application

of

untargeted,

holistic

approaches

such

us

metabolomics/lipidomics. Acquired data is analysed to find significant signals responsible for the differentiation between investigated conditions. Subsequently identification has to be performed to bring biological meaning to the obtained results. Lipid identification seems to be relatively easy due to the known characteristic fragments, however large number of structural isomers and the formation of different adducts, makes it challenging and at risk of misidentification. The inspection of data, acquired for plasma samples by a standard metabolic fingerprinting method, revealed multi-signals formation for phosphatidylcholines, phosphatidylethanolamines and sphingomyelines by formation of such ions as: [M+H]+, [M+Na]+, [M+K]+ in positive ionisation mode, [M-H]-, [M+HCOO]- and [M+Cl]- in negative mode. Moreover sodium formate cluster formation was found for [M+H.HCOONa]+ and [HH.HCOONa]-. The MS/MS spectrum obtained for each of the multi-ions revealed significant differences in the fragmentation, which were confirmed by analysis of the samples in two independent research centres. After inspection of an acquired spectra, a list of characteristic and diagnostic fragments was proposed; which allowed for easy, quick and robust lipid identification providing information about the head group, formed adduct and fatty acyl composition. This ensures successful identification which is of great importance for contextualisation of data and results validation.

Key words: phospholipids; Phosphatidylcholine; Phosphatidylethanolamine; Sphingomyelin; fingerprinting; ionisation; adduct formation; fragmentation; CID; structural elucidation.

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INTRODUCTION

Living cells, and subsequently organisms, are mainly composed of lipids, the number of which in mammalian cells can exceed thousands 1. Phospholipids (PLs) play several roles within organism, being often key metabolites in many pathways, either in health or in disease. PLs are the major components of the biological membranes contributing to their biochemical and biophysical properties. Alterations in the degree of unsaturation in acyl side chains, for instance, can affect membrane fluidity2, 3. In many organisms, such alterations are significant for adaptation to changes in temperature and to the presence of xenobiotics 4. Additionally, PLs modulate membrane trafficking and are precursors for many functional molecules. Metabolites derived from the PLs degradation are important intracellular signalling molecules involved in such processes as proliferation and apoptosis 5. Recently, extensive application of metabolomics and lipidomics to study human diseases has revealed that changes in particular classes of lipids or even particular lipid metabolites are characteristic to different pathologies

6-8

. New discoveries were possible because of the

progress in metabolomics/lipidomics approaches. The researchers are making an effort in order to improve current methodologies and to increase the number of lipids detected in one analytical run. These improvements affect at different steps of analytical process, which include novel extraction methods

9

or improvement in chromatographic conditions

10

.

However acquisition of lipids m/z is meaningless without proper identification. Unidentified molecules are not informative and no conclusions can be drawn. On the other hand, wrong identification can even have a worse impact leading to false biochemical interpretation where subsequently the whole data contextualisation process fails, affecting the final outcome of the entire workflow. Novel computational strategies 11 and search tools 12 have been proposed to accelerate identification; however, they are based only on mass accuracy. According to the Metabolomics Standards Initiative (MSI)

13

, the highest levels of

identification confidence are achieved by tandem MS analyses. Obtained MS/MS spectrum can be searched against databases and compared with the one available in the library or with the one acquired for the corresponding standard. Strongly limited availability of commercial standards causes that MS/MS databases play a very important role in fragmentation pattern recognition. Following fragmentation patterns is particularly useful for groups of molecules with similar structures and physical and chemical properties; the best examples of which are lipids. Currently, several papers describing the identification of PLs based on the fragmentation pattern in electrospray tandem mass spectrometry (ESI-MS/MS) have been 3

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published. Different types of tandem mass analysers, including quadruple-time of flight (QTOF)

14, 15

, triple quadruple (QQQ)

5, 16-18

or quadruple-ion trap (Q-TRAP)

19

were used to

study fragmentation pattern of phospholipids. PLs are composed of a polar group and fatty acid chain(s) (Figure 1). Fragments characteristic to

the

polar

heads

phosphatidylethanolamine,

of PE;

different

lipid

classes

phosphatidylserine,

PS;

(phosphatidylcholine,

PC;

phosphatidylinositole,

PIs;

phosphatidic acid, PA; phosphatidylglycerol, PG; and sphingomyelins, SM) as well as for a fatty acyl (FA) chains have been reported. PL identification is challenging due to a large number of structural isomers and formation of different ions with various adducts. Moreover, the presence of characteristic fragments, but with ambiguous or absent diagnostic fragments causes frequent misidentification, where although the molecule is properly assigned to the class e.g. PC or PE, it is identified as a different molecule with a different composition of fatty acids and number of double bonds. As the length of carbon chains has a direct impact on the lipid properties and the unsaturation level directly affects the possibility of oxidation, such misidentification leads to wrong interpretation of data and it will result in a failure of validation by targeted analysis. In this paper, the identification of PLs in LC-ESI-Q-TOF MS/MS-based metabolomics studies will be discussed, highlighting the changes in fragmentation pattern regarding the different adduct formations and specifying diagnostic fragments and/or neutral losses. PCs and PEs as the major PLs both in the number of species as well as their abundance in plasma

20

were

selected to investigate PLs ionisation, adduct formation and fragmentation. Although SMs belong to a different category of lipids (Sphingolipids), they were also investigated since they are sphingolipid analogues of phosphatidylcholines (Figure 1), that contain phosphorylcholine attached to a ceramide 5, causing them to behave similarly to PCs in CID. The structural elucidation of unknown metabolites is challenging and time consuming. In case of metabolomics and lipidomics studies, the number of molecules requiring proper identification often extents dozens if not hundreds. Therefore we propose a robust and quick method to determine the category of lipids, ionisation adduct and composition of fatty acids. Information obtained in this way enables proper and successful identification, minimising the risk of misidentification.

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MATERIALS AND METHODS

Chemical and reagents Ultrapure water, used to prepare all the aqueous solutions was obtained “in-house” from a Milli-Qplus185 system (Millipore, Billerica, MA, USA). LC-MS acetonitrile and analytical grade formic acid were purchased from Fluka Analytical (Sigma-Aldrich Chemie GmbH, Steinheim, Germany).

Analytical set-up Analyses were performed in two laboratories: i) CEMBIO at San Pablo CEU University in Madrid, Spain employing 6550 iFunnel Q-TOF (Agilent Technologies); ii) Medical University of Bialystok (MUB), Poland using 6540 UHD Q-TOF (Agilent Technologies). Both mass spectrometers were coupled to a 1290 Infinity UHPLC systems (Agilent Technologies). During all analyses two reference masses were used: m/z 121.0509 (protonated purine) and m/z 922.0098 (protonated hexakis (1H, 1H, 3H-tetrafluoropropoxy) phosphazine (HP-921)) for positive ionization mode and m/z 112.9856 (proton abstracted TFA anion) and m/z 966.0007 (formate adduct of HP-921) for negative mode. These masses were continuously infused to the system to allow constant mass correction.

Metabolic fingerprinting with LC-MS Sampling and sample preparation The study was performed on the plasma pool obtained from healthy volunteers. Blood samples were taken in a fasting state, EDTA anti-coagulated blood was centrifuged at 1000 × g for 10 min at 4ºC. Plasma pool was stored in aliquots at -80ºC until the day of analysis. Plasma samples were prepared using the extraction method, which has been successfully employed for plasma metabolic fingerprinting 9, 21.

Samples analysis Samples were analysed applying identical chromatographic conditions 21, 22. Extracted plasma samples (0.5µL) were injected onto the Zorbax Extended-C18 Rapid Resolution (Agilent) (2.1 × 50 mm, 1.8 µm) column thermostated at 60ºC. Metabolites were eluted at 0.6 mL/min flow rate with solvent A, water with 0.1% formic acid, and solvent B, acetonitrile with 0.1% formic acid. The gradient started from 5% B for the first min, then to 80% by 7 min, then to

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100% by 11.5 min, and returned to starting conditions in 0.5 min, keeping the re-equilibration until 15 min. Data were collected in ESI positive (+) and negative (-) ionisation modes in separate runs on a Q-TOF operated in full scan mode from 100 to 1000 m/z. The scan rate of 1.5 scans per second was used in both polarities, on the MS and MS/MS levels. The nozzle voltage was set to 1000 V; capillary voltage to 3000 V for positive and 4000 V for negative ionisation mode. The drying gas was heated up to 250ºC and flowed at the rate of 12 L/min. To enhance ionisation of non-polar molecules, additional heating was applied by the use of sheath gas, heated up to 370ºC with a flow 11 L/min. For the tandem MS/MS analysis experiments were repeated with identical chromatographic conditions to the primary analysis. Ions were targeted for CID fragmentation on the fly based on the previously determined accurate mass and retention time. To ensure comparable fragmentation patterns, a fixed collision energy was used, applying 20 eV to all targeted ions, however all findings were confirmed also with the data obtained working with the slope to determine collision energy. The collision cell gas flow was the same for all analyses and set to 18 psig.

Data treatment and identification Lipid identification was performed by: i) manual MS/MS spectra interpretation; ii) comparison of MS/MS spectra acquired with spectra available in following databases: METLIN

(http://metlin.scripps.edu/index.php),

LipidMaps

(http://www.lipidmaps.org),

LipidBank (http://lipidbank.jp/) and an in-house built database; iii) product ion structure elucidation by use of MassHunter Molecular Structure Correlator (MSC, Agilent B.05.00) and ChemSketch MS Fragmenter (ACD/Labs, v.12). To present and visualise the results, several different softwares and applications were used. All structures were drawn using MarvinSketch (http://www.chemaxon.com). Spectra presented within the paper were processed through Target MS/MS search in Mass Hunter Qualitative software (Agilent, B.06.00). The algorithm applied creates a list of all targeted m/z values in the data file and subsequently extracts a chromatogram of the MS/MS product ion data with that precursor ion m/z. To exclude matrix related ions from the spectra, peak spectrum background was subtracted (an average of spectra at peak start and end). Reprocessed MS/MS data were inspected and cleaned of unrelated ions using Personal Compound Database and Library Manager (PCDL, Agilent B.04.00). Product ions described within this publication do not represent the only ones that could be observed, but those that 6

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were commonly observed across many spectra and considered as structurally relevant. Low abundant fragments were confirmed by the use of a novel algorithm (publication in preparation) which helps to distinguish between parent ion-related fragments and random, unrelated signals. RESULTS AND DISCUSSION Compound identification is indicated as the biggest bottleneck in metabolomics studies (http://metabolomics.us/2009/ASMS/MetabolomicsWorkshop/SurveyResults/) which reflects its importance and also highlights the associated challenge. Although lipid fragmentation can be easily predicted, a large number of structural isomers and formations of different ions make their identification challenging. In the present study plasma samples were fingerprinted employing LC-QTOF-MS equipped with Jetstream ESI source. Acquired data was investigated to find signal corresponding to the PC, PE and SM with an assumption of multi-adduct ionisation. Data revision revealed that all targeted lipids were ionised in several different ways ([M+H]+, [M+Na]+, [M+K]+ in positive ESI mode and [M-H]-, [M+Cl]-, [M+HCOO]- for negative ESI mode). Also formation of HCOONa cluster for PC in positive ionisation mode and for PE in negative ionisation mode was observed. In positive ionisation mode all PCs and SMs were observed with three adducts: H+, Na+ and K+. Lipids ionised by sodium give for SM a signal smaller than [M+H]+ but higher than [M+K]+. For PC, the [M+Na]+ signal was also higher than for [M+K]+, however in many cases it was comparable or just slightly lower than the [M+H]+ (Figure 2). In some cases, the signal for potassium was missed due to the low concentration of the particular lipid in the sample. For PE, the potassium adduct was not observed and the signal given by the protonated form was always the highest one. In negative ionisation mode, most PCs and SMs were ionised with both adducts: formate and chloride. In such cases signal given by formate attached to the molecule was always higher than the signal generated by the chloride adduct, what can be explained by presence of formic acid in the mobile phase. However in some cases only chloride or only formate adducts were observed. For PE in the negative CID spectra, the chloride adduct was not observed. PE ionised by deprotonation and formate attachment were commonly observed giving comparable or higher signal for [M+HCOO]- form. All information obtained about characteristic and diagnostic fragments is provided in two ways: summary of essential

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information in the form of tables (Table 1, Table 1S-3S) and exhaustive description of adduct formation and fragmentation (Supplementary Information - comments). All found ions, corresponding to exactly the same molecule, were targeted for CID MS/MS analysis. Obtained spectra were interpreted and identifiers (ID) were assigned to each obtained spectrum. Only those with the same ID derived from the interpretation (both in terms of lipid category and composition of fatty acids) were considered for final data interpretation and construction of conclusions. Moreover spectra, which revealed fragments corresponding to two categories of lipids (e.g. PC and PE), indicating co-elution, were not included for the final data interpretation and drawing of conclusions. Each spectrum was divided into three regions: low-mass region, where head group-related ions are observed; mid-mass region, where fatty acids related fragments are detected and high-mass region, where molecular ions and neutral losses are observed. To prove identification, different forms of cations and anions were targeted for the same molecule. The interpretation of each obtained spectrum lead to the same ID not only in terms of belonging to the same lipid category, but moreover in terms of fatty acids composition, which together gives a robust and complete identification. Furthermore, a novel algorithm (publication in preparation) was applied to determine which of the signals across CID spectra correspond to the parent ion, and which ions are random and unrelated (particularly at the noise level). As mentioned above, some of the examples of fragmentation are illustrated based on exactly the same species ionised by different adducts. This strategy was impossible to follow in the case of some molecules because they give only one signal (e.g. some PCs were ionised only with formate while others only with chloride). Theoretically, this can be explained through two facts: first it is related to the properties of ESI itself, which is known to give not fully reproducible results – the ionisation mechanism depends on the mobile phases and sample, therefore any slight differences in their composition (during fingerprinting studies a gradient method is applied) can lead to the differences in ionisation. A second hypothesis is related to the ionised molecule: although all PCs or PEs are very similar in terms of their physico-chemical properties, the differences related with the chain length, number and position of double bonds affects structural conformation. Multidimensional organisation of the molecule can affect the possibility of some adduct formations through the space restriction in the case of lipid folding. All elucidated structures, explained fragments and neutral losses are presented in Figures 3-8 illustrating representative spectra for each category of lipids in each investigated ionisation manner. Findings were confirmed analysing samples in two independent research centres (CEMBIO and MUB). Moreover, diagnostic and characteristic fragments and losses are 8

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presented in Table 1 (summarised data) and in Tables 1S-3S (Supplementary InformationTables), where all adducts and losses are listed with their formulas and monoisotopic masses displayed with four decimals. Such detailed information is given for the first time and can be particularly helpful for any kind of data acquired with high accuracy mass spectrometry. Each fragment and loss is also described, stating information about its frequency and contribution to the entire identification process. The results that are presented below, for each class of lipids, contain only the most relevant information, while a thorough description is stated in Supplementary Information – Comments. This is due to the large amount of information required to be presented, arising from the broad range of investigated aspects (three classes of lipids, two polarities, multiadducts).

Phosphatidylcholines Phosphatidylcholines were detected in both ionisation modes. In positive ionisation mode being cationised by hydrogen, sodium and potassium (Figure 3), while in negative ionisation mode being anionised by formate and chloride (Figure 4). PC ionised by deprotonation was not observed which can be explained by the ‘fixed positive charge’ quaternary alkyl ammonium group within the phosphocholine group

19

. Moreover an interesting cluster of

sodium formate (later called cluster) was observed for PC being previously ionised by hydrogen.

Positive ionisation mode In the low-mass region phosphate-related ions are observed: i) m/z 125.0009 [M+H]+ protonated phosphate (most likely as a five-membered cyclophosphane ring [23]); ii) m/z 146.9817 [M+Na]+-sodiated phosphate; iii) m/z 162.9557 [M+K]+-potassiated phosphate; iv) m/z 184.0733 [M+H]+- protonated phosphocholine. In the mid-mass region two kinds of fatty acyl related fragments are observed: lyso-form for each fatty acid (e.g. for PC(16:0/20:5), it will be PC(16:0/0:0) and PC(0:0/20:5)) and its corresponding form with water loss. The last region of MS/MS spectrum is the region of neutral losses: i) m/z 59.0734trimethylamine; ii) m/z 67.9874- sodium formate; iii) m/z 127.0596- trimethylamine with sodium formate; iv) m/z 183.0670- phosphocholine; v) m/z 205.0479- phosphocholine with sodium; vi) m/z 221.0219- phosphocholine with potassium; vii) m/z 251.0537-

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phosphocholine with sodium formate and viii) m/z 273.0366- phosphocholine with sodium and with sodium formate. PC ionisation by hydrogen is commonly observed for ESI and such cationisation is usually reported

16

. Ionisation by sodium is rather rare and was exceptionally described

17

, while

ionisation by potassium is reported for the first time. It is particularly interesting because sodiated and potassiated forms are well known and deeply investigated for MALDI-MS

23-25

and FAB-MS 26. Moreover, ionisation by hydrogen accompanied by sodium formate cluster is reported for the very first time for phosphatidylcholines. Studying the product ions generated through tandem MS for PC ionised by different cations some patterns can be distinguished. The differences observed between spectra are related to the difference in the mass of cation and sub-consequently fragment and/or loss generated. A comparison of all CID spectra revealed a decreasing degree of fragmentation in the order: [M+H]+ > [M+K]+ > [M+Na]+, which in case of hydrogen and sodium adduct was showed in previous studies27. The other noticeable difference is neutral loss for sodiated and potassiated PC in comparison to protonated PC. This difference concerns both, the number of losses formed as well as their signal. Investigating spectra and their differences between adducts diagnostic fragments and losses can be recognised: fragments m/z 146.9817 [M+Na]+ and m/z 162.9557 [M+K]+ as well as losses m/z 205.0479 and m/z 221.0219. Presence of these signals can be used for a reliable indication of ionisation with sodium and potassium. Easy recognition of adducts is particularly important because each molecular ion (m/z 780.5529 [M+H]+ for [PC(20:5/16:0)+H]+, m/z 802.5347[M+Na]+ for [PC(20:5/16:0)+Na]+ and m/z 818.5089 [M+K]+ for [PC(20:5/16:0)+K]+) if considered as [M+H]+ can be putatively identified as a PC because each of them gives a hit when searched against the databases. However the ID obtained corresponds to different PC, due to the difference in the number of double bonds and fatty acyl chain length. Sodium formate cluster can be easily recognised through the neutral losses of m/z 67.9874, m/z 251.0537 and m/z 273.0366. Domination of the fragment m/z 146.9817 in the low-mass region is also an assignation of the presence of cluster.

Negative ionisation mode In the low-mass region phosphate-related ions are observed among which we detected: i) m/z 168.0458 [M-H]-- deprotonated demethylated phosphocholine; ii) m/z 224.0693 [M-H]-demethylated phosphocholine dehydrated glycerol ester and iii) m/z 242.0798 [M-H]-demethylated phosphocholine glycerol ester. 10

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The mid-mass region is the most interesting one from a diagnostic point of view, where three kinds of fragments can be found: i) deprotonated fatty acid (FA) fragment corresponding to each of fatty acid constituting PC [M-H]-; ii) demethylatedlysophosphatidylcholine (LPCCH3) [M-H]- and iii) demethylatedlysophosphatidylcholine with water loss (LPC-CH3-H2O) [M-H]-. The last region of high-masses corresponds to neutral losses. For PC ionised with chloride and formate this region is crucial for ionisation adduct determination: i) m/z 60.0222- methyl formate and ii) m/z 49.9926 - methylated chloride. Comparing spectra acquired for PC ionised as [M+HCOO]- and [M+Cl]-, big differences cannot be observed. The fragmentation pattern is the same and the most relevant differences refer to the neutral losses. The head related fragment of m/z 168.0358 can be assumed as a diagnostic fragment for PC and can be supported by fragments m/z 224.0693 and 242.0798. However these fragments should be carefully used as they are not always observed: presence of them is encouraging PC identification, however their absence should not be an indication for PC ID rejection. Fatty acids related signals, especially [FA-H]- are diagnostic fragment for exact fatty acyls composition. The neutral loss of m/z 60.0222 (HCOO-CH3) and m/z 49.9926 (CH3-Cl) can be used as a diagnostic loss for robust adduct determination. Comparing degree of fragmentation it can be concluded that chloride form is stronger fragmented then the formate form [M+Cl]-> [M+HCOO]- . Such conclusion can be driven regardless comparison of the parent ions or the very first fragments formed through neutral loss of methylated adduct.

Phosphatidylethanolamines Phosphatidylethanolamines were detected in both ionisation modes. In positive ionisation mode PE were cationised by hydrogen and sodium (Figure 5). In contrast to PC potassium adduct was not observed. In negative ionisation mode PE were detected being anionised by deprotonation and formate attachment (Figure 6). As opposed to the PCs and SMs, for PEs chloride adduct was not observed. This may be explained by the fact that phosphocholine contains ammonium quaternary salt while phosphoetanolamine primary ammonium salt which has more acidic properties. Moreover the cluster of sodium formate was observed this time in negative ionisation mode with previously deprotonated PE.

Positive ionisation mode

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In the low-mass region, head related fragments were observed: i) m/z 120.9660 [M+Na]+ sodiated form of phosphoric acid and ii) m/z 164.0083 [M+Na]+phosphoethanolamine ionised with sodium. In the mid-mass region, fatty acid related fragments can be detected. The observed product ions correspond to the neutral loss of each of fatty acyl chain (e.g. PE(16:0/20:4)-FA(16:0) and PC(16:0/20:4)-FA(20:4)) which can be calculated as a PE-FA2 or FA1-H+58.0418 Da. The high-mass region is the most informative for PE detected in positive ionisation mode. In this region interesting neutral losses are observed, which are very useful for both, determination of lipid category as well as for the adduct definition: i) m/z 18.0105- water; ii) m/z 43.0340 -vinylamine; iii) m/z 59.0371- trimethylamine; iv) m/z 141.0191phosphoethanolamine and v) m/z 164.0010-phosphoethanolamine with sodium. Comparing CID spectra obtained for protonated and sodiated PE clear differences can be notice. This makes differentiation between ions relatively easy. Neutral loss of m/z 141.0191 is a diagnostic fragment for PEs as well as fragment m/ 164.0010. However due to the low intensity of phosphoethanolamine ionised with sodium for protonated form this fragment is not recommended as a diagnostic one but rather characteristic one. Fragment m/z 120.9660 and neutral loss of m/z 164.0010 can be used as indicators of sodium adduct formation. In contrast to the PC, PE shows the opposite manner of fragmentation. Comparison of all CID spectra revealed a decreasing degree of fragmentation in the order [M+Na]+> [M+H]+.

Negative ionisation mode In low-mass region head related fragments are observed: i) m/z 140.0118 [M-H]-deprotonated phosphoethanolamine; ii) m/z 168.0431 [M-H]-- deprotonated

ethanol-

-

ethylamine phosphate; iii) m/z 196.0380 [M-H] - deprotonated doubly dehydrated glycerolphosphocholine. In the mid-mass region fatty acids related fragments appear: i) fatty acyl fragments (FA) corresponding to each of fatty acids constituting PC [M-H]-; ii) lyso-phosphatidylcholine (LPC-H) [M-H]-; iii) lysophosphatidylcholine with water loss (LPC-H-H2O) [M-H]-. The last region contains information about neutral losses. In contrast to the positive ionisation mode, the number of neutral losses observed in a negative MS/MS spectrum is low: i) m/z 60.0222- methyl formate and ii) m/z 67.9874- methylated chloride. Designation of the degree of fragmentation for PE is not easy. Comparing the residual signal of parent ions it can be assumed that both formate adduct and sodium formate cluster have higher degree of fragmentation than the PE ionised by deprotonation. However, it is important 12

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to consider the fact that all fragments are generated from the fragment obtained through the neutral loss therefore to reveal the degree of real fragmentation, these signals should be compared. Following this, subsequent order can be established: [M-H]-> [M+HCOO]- ≈[MH.HCOONa]-. Comparing CID spectra obtained for PE ionised by different ions, diagnostic fragments and losses can be selected: formate adduct can be determine through the fragment of m/z 168.0431 and neutral loss of m/z 60.0222. Deprotonated PE and deprotonated PE with cluster can be recognised through two fragments: m/z 140.0118 and m/z 196.0380. To distinguish between two deprotonated forms, a neutral loss of m/z 67.9874 can be used as an indicator of sodium formate cluster. To determine composition of fatty acyls, signals corresponding to the [FA-H]can be used with (if possible) supporting information from lyso-forms.

Sphingomyelin Sphingomyelines were detected in both ionisation modes. In positive ionisation mode they were cationised by hydrogen, sodium and potassium (Figure 7), while in negative ionisation mode they were anionised by formate and chloride (Figure 8). As in the case of phosphatidylcholines, sphingomyelines anionised by deprotonisation were not observed, due to the permanent positive charge within the phosphocholine head. In contrast to the PC and PE sodium formate cluster was not found.

Positive ionisation mode The low-mass region contains the phosphate-related ions: i) m/z 125.0009 [M+H]+protonated phosphate; ii) m/z 146.9817 [M+Na]+-sodiated phosphate; iii) m/z 162.9557 [M+K]+-potassiated phosphate; iv) m/z 166.0627 [M+H]+- protonated dehydrated phosphocholine and v) m/z 184.0733 [M+H]+- protonated phosphocholine. In the mid-mass region the only fragment observed corresponds to the long chain base which is a sphingosine backbone fragment. In this particular case it is m/z 264.270 and it indicates d18:1 chain (m/z 264.2685) presence. The list of fragments (m/z) corresponding to the most common long chains is listed in Table 8S (Supplementary Information-Tables). The high-mass section is really interesting and plays an important role in the adduct determination. Several neutral losses can be distinguished: i) m/z 18.0105- water; ii) m/z 59.0734-

trimethylamine;

iii)

m/z

183.0670-

phosphocholine;

iv)

m/z

205.0479

phosphocholine with sodium and v) m/z 221.0219- phosphocholine with potassium.

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Evaluation of all CID spectra revealed a degreasing degree of fragmentation of SM in the order: [M+H]+> [M+K]+ > [M+Na]+, which is in compliance with the order observed for PC. This phenomenon confirms the similarity of structures and therefore properties of PC and SM. Comparing the spectra acquired for different adducts for SMs several conclusions can be drown: a fragment of protonated phosphocholine can be assigned as a diagnostic fragment for SM in general. This identification can be supported by other head related signals such as m/z 125.0009, m/z 146.9817 and m/z 162.9557, where 146.9817 is also an indication of sodium presence while m/z 162.9557 of potassium adduct. Signal found in the mid-mass region, corresponding to the long chain base, is very useful for the accurate structure elucidation regardless the ionisation way. Neutral loss of m/z 59.0734 can be assumed as a diagnostic loss for another adduct than hydrogen. If the signal from parent ion is high enough, fragments m/z 205.0479 and m/z 221.0219 may be used in sodium and potassium adduct recognition.

Negative ionisation mode The MS/MS spectra acquired for SM in negative ionisation mode are the simplest and least informative in comparison to all others. In the low-mass region only one head-related fragment was observed: m/z 168.0358 [M-H]- being deprotonated dimethylamino-phosphate. In the mid-mass region no fragments were observed. In the high-mass region neutral losses were observed: i) m/z 60.0222- methyl formate and ii) m/z 49.9926- methylated chloride. As in the previous cases, both losses are really useful for the adduct determination. Studying the CID spectra obtained for both adducts, it can be concluded that the fragment m/z 168.0358 can be assumed as a diagnostic fragment for SM. Unfortunately no fatty acid amide related fragments were observed which makes meticulous identification impossible. The region of neutral losses revealed only one loss but essential for the ionization adduct determination. Comparison of both, parent ion and the fragment formed through the neutral loss revealed high similarity in terms of the degree of fragmentation between SM ionised by formate and chloride attachment: [M+HCOO]- ≈[M+Cl]-.

The product ions obtained for PCs and SMs are very similar and therefore particular attention to highlight the differences in the fragmentation pattern will be paid to them. In positive ionisation mode fragmentation pattern is very similar and the only one difference, which can be assumed for the diagnostic purposes, is related to the mid-mass region: for PC in this region lysophosphatidylcholines and dehydrated lysophosphatidylcholines are observed, 14

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while for SM long chain basees are detected. In negative ionisation mode the distinction between PC and SM is easier. Although fragmentation is similar and most of the fragments are common between these two categories of lipids, some diagnostic patterns can be specified: the fragment of m/z 168.0358 corresponding to the demethylated phosphocholine can be assumed as an indicator of the SM. Although this fragment also appears in the PC spectra, its intensity is rather low, while in case of SM it dominates the spectra. Another noticeable difference refers to the lack of fatty acyl related fragments in the CID spectrum acquired for SM, while for PC, the signal given by fatty acids dominates the spectra. Scrupulous identification of PCs and PEs requires information about fatty acyls composition. The difference in the identifiers obtained through the exact mass of parent ion and through the fatty acids composition is, most likely, an indication of wrongly assigned neutral mass and another adducts and/or clusters have to be considered. To help the exact fatty acids determination the tables (Table 1S-7S, Supplementary Information) with the most common fatty acids were prepared. Tables contain: the neutral mass for each fatty acids, m/z for protonated and deprotonated form, m/z for corresponding lyso- form, both for LPC and LPE species, m/z for the form with 58.0418 Da, m/z for demethylated form, m/z for demethylated and dehydrated form, m/z for dehydrated form. Such tables should be a helpful tool for easy and quick determination of fatty acids composition which is crucial for proper identification of lipids. In case of SMs such identification can be done based on the information about the long chain base. The two most commonly found chains correspond to the d18:1 (m/z 264.2685) and d18:0 (m/z 266.2842). To help with identification of SMs consisting of other dchains, list of 8th the most possible chains is presented in Table 8S (Supplementary Information). Inspecting spectra obtained for PC, PE and SM it can be concluded that sodiated and potassiated forms give more informative CID spectra in the fragmentation process than the protonated precursor ion. The signal obtained for different ions, e.g. [M+H]+, [M+Na]+ and [M+K]+ should be merged for statistical purposes (multi-signals coming from the same molecule skew the data and therefore statistical output), however it seems that the individual consideration of each generated ion greatly improve identification. Each ion brings some information which help to minimize or even to avoid risk of misidentification.

CONCLUSIONS Obtained results show that PC, PE and SM analysed under standard metabolomics conditions are ionised with different adducts resulting in multi-signals. Most of the data re-processing 15

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software combines adducts corresponding to the same molecule; however most of them fail whenever the protonated (in positive ionisation mode) or deprotonated (negative ionisation mode) form is missed. This leads to the situation where the same molecule is represented by several different features. For data treatment purposes each of multi-signals should be combined into one value, therefore proper identification is necessary to know which signals should be merged. Moreover, for identification purposes individual consideration of each generated ion greatly improves identification. Each fragmented ion brings additional (unique) information which complements detailed identification. The proposed methodology has already been successfully applied to study several diseases where phospholipid alterations were found, including abnormal birth weight in healthy pregnancies22, gestational diabetes and studies about the relationship between body mass index and type 2 diabetes mellitus. Spectra acquired in negative ionisation mode showed ionisation through deprotonation but also formate and chloride attachment. In positive ionisation mode, apart from a protonated molecular ion, sodiated and potassiated forms were also found. In both ionisations sodium formate cluster was found. Inspection of the MS/MS spectra acquired for ions with different adducts revealed significant differences in the fragmentation pattern. Novel fragments, not previously reported for phospholipids ionised using ESI, were found. Observations reported in this study help to minimize or even avoid the risk of lipids misidentification. Although many of presented observations have been already reported for different ionisation techniques (e.g. for FAB-MS or MALDI-MS) for the first time so complex information is presented within single publication covering simultaneously three lipid categories analysed in both polarity modes for so many adducts generated by use of ESI-Q-TOF-MS. By combining information acquired for different ions in both ionisation modes complete identification can be performed. All selected signals (both, fragments and neutral losses) are summarised in Table 1. The information presented is divided into positive and negative ionisation mode but also into PC, PE and SM. Within each lipid group different adducts and clusters are listed. The proposed diagnostic and characteristic fragments and neutral losses can be used for robust and quick identification of PCs, PEs and SMs.

ACKNOWLEDGEMENTS The study was supported by the funding from the Spanish Ministry of Science and Technology (MCIT CTQ2011-23562) and Polish Ministry of Science and Higher Education (KNOW 2012-2017). 16

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“Supporting Information Available: This material is available free of charge via the Internet at http://pubs.acs.org.”

Tables from Supporting Information-Tables: Table 1S: Diagnostic and characteristic fragments for PC identification in positive ionisation mode (Panel A) and in negative ionisation mode (Panel B). Table 2S: Diagnostic and characteristic fragments for PE identification in positive ionisation mode (Panel A) and in negative ionisation mode (Panel B). Table 3S: Diagnostic and characteristic fragments for SM identification in positive ionisation mode (Panel A) and in negative ionisation mode (Panel B). Table 4S: Saturated fatty acids (FA) and its corresponding lyso-phosphatidylcholines (LPC) and lyso-phosphatidylethanolamines (LPE). Table 5S: Monounsaturated fatty acids (FA) and its corresponding lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). Table 6S: Diunsaturated fatty acids (FA) and its corresponding lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). Table 7S: Triunsaturated fatty acids (FA) and its corresponding lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). Table 8S: Tetraunsaturated fatty acids (FA) and its corresponding lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). Table 9S: Pentaunsaturated fatty acids (FA) and its corresponding lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). Table 10S: Hexaunsaturated fatty acids (FA) and its corresponding lysophosphatidylcholines (LPC) and lysophosphatidylethanolamines (LPE). Table 11S: m/z for the fragment corresponding to the long chain base observed in the MS/MS spectrum obtained in positive ionisation mode for sphingomyelins.

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REFERENCES 1. van Meer, G., Cellular lipidomics. EMBO J 2005, 24, (18), 3159-65. 2. Hilvo, M.; Denkert, C.; Lehtinen, L.; Müller, B.; Brockmöller, S.; Seppänen-Laakso, T.; Budczies, J.; Bucher, E.; Yetukuri, L.; Castillo, S.; Berg, E.; Nygren, H.; Sysi-Aho, M.; Griffin, J. L.; Fiehn, O.; Loibl, S.; Richter-Ehrenstein, C.; Radke, C.; Hyötyläinen, T.; Kallioniemi, O.; Iljin, K.; Oresic, M., Novel theranostic opportunities offered by characterization of altered membrane lipid metabolism in breast cancer progression. Cancer Res 2011, 71, (9), 3236-45. 3. Pietiläinen, K. H.; Róg, T.; Seppänen-Laakso, T.; Virtue, S.; Gopalacharyulu, P.; Tang, J.; Rodriguez-Cuenca, S.; Maciejewski, A.; Naukkarinen, J.; Ruskeepää, A. L.; Niemelä, P. S.; Yetukuri, L.; Tan, C. Y.; Velagapudi, V.; Castillo, S.; Nygren, H.; Hyötyläinen, T.; Rissanen, A.; Kaprio, J.; Yki-Järvinen, H.; Vattulainen, I.; Vidal-Puig, A.; Orešič, M., Association of lipidome remodeling in the adipocyte membrane with acquired obesity in humans. PLoS Biol 2011, 9, (6), e1000623. 4. Al-Saad, K. A.; Zabrouskov, V.; Siems, W. F.; Knowles, N. R.; Hannan, R. M.; Hill, H. H., Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry of lipids: ionization and prompt fragmentation patterns. Rapid Commun Mass Spectrom 2003, 17, (1), 87-96. 5. Milne, S.; Ivanova, P.; Forrester, J.; Alex Brown, H., Lipidomics: an analysis of cellular lipids by ESI-MS. Methods 2006, 39, (2), 92-103. 6. Whiley, L.; Sen, A.; Heaton, J.; Proitsi, P.; García-Gómez, D.; Leung, R.; Smith, N.; Thambisetty, M.; Kloszewska, I.; Mecocci, P.; Soininen, H.; Tsolaki, M.; Vellas, B.; Lovestone, S.; Legido-Quigley, C., Evidence of altered phosphatidylcholine metabolism in Alzheimer's disease. Neurobiology of Aging 35, (2), 271-278. 7. Oresic, M.; Hyotylainen, T.; Herukka, S. K.; Sysi-Aho, M.; Mattila, I.; SeppananLaakso, T.; Julkunen, V.; Gopalacharyulu, P. V.; Hallikainen, M.; Koikkalainen, J.; Kivipelto, M.; Helisalmi, S.; Lotjonen, J.; Soininen, H., Metabolome in progression to Alzheimer's disease. Transl Psychiatry 2011, 1, e57. 8. Cui, L.; Lee, Y. H.; Kumar, Y.; Xu, F.; Lu, K.; Ooi, E. E.; Tannenbaum, S. R.; Ong, C. N., Serum Metabolome and Lipidome Changes in Adult Patients with Primary Dengue Infection. PLoS Negl Trop Dis 2013, 7, (8), e2373. 9. Whiley, L.; Godzien, J.; Ruperez, F. J.; Legido-Quigley, C.; Barbas, C., In-vial dual extraction for direct LC-MS analysis of plasma for comprehensive and highly reproducible metabolic fingerprinting. Anal Chem 2012, 84, (14), 5992-9. 10. Retra, K.; Bleijerveld, O. B.; van Gestel, R. A.; Tielens, A. G. M.; van Hellemond, J. J.; Brouwers, J. F., A simple and universal method for the separation and identification of phospholipid molecular species. Rapid Communications in Mass Spectrometry 2008, 22, (12), 1853-1862. 11. Jones, J.; Stump, M.; Fleming, R.; Lay, J.; Wilkins, C., Strategies and data analysis techniques for lipid and phospholipid chemistry elucidation by intact cell MALDI-FTMS. Journal of the American Society for Mass Spectrometry 2004, 15, (11), 1665-1674. 12. Blanchard, A. P.; McDowell, G. S. V.; Valenzuela, N.; Xu, H.; Gelbard, S.; Bertrand, M.; Slater, G. W.; Figeys, D.; Fai, S.; Bennett, S. A. L., Visualization and Phospholipid Identification (VaLID): online integrated search engine capable of identifying and visualizing glycerophospholipids with given mass. Bioinformatics 2013, 29, (2), 284-285. 13. Sumner, L.; Amberg, A.; Barrett, D.; Beale, M.; Beger, R.; Daykin, C.; Fan, T. M.; Fiehn, O.; Goodacre, R.; Griffin, J.; Hankemeier, T.; Hardy, N.; Harnly, J.; Higashi, R.; 18

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Kopka, J.; Lane, A.; Lindon, J.; Marriott, P.; Nicholls, A.; Reily, M.; Thaden, J.; Viant, M., Proposed minimum reporting standards for chemical analysis. Metabolomics 2007, 3, (3), 211-221. 14. Dong, J.; Cai, X.; Zhao, L.; Xue, X.; Zou, L.; Zhang, X.; Liang, X., Lysophosphatidylcholine profiling of plasma: discrimination of isomers and discovery of lung cancer biomarkers. Metabolomics 2010, 6, (4), 478-488. 15. Hou, W.; Zhou, H.; Bou Khalil, M.; Seebun, D.; Bennett, S. A.; Figeys, D., Lyso-form fragment ions facilitate the determination of stereospecificity of diacyl glycerophospholipids. Rapid Commun Mass Spectrom 2011, 25, (1), 205-17. 16. Hsu, F. F.; Turk, J., Electrospray ionization/tandem quadrupole mass spectrometric studies on phosphatidylcholines: the fragmentation processes. J Am Soc Mass Spectrom 2003, 14, (4), 352-63. 17. Han, X.; Gross, R. W., Structural Determination of Lysophospholipid Regioisomers by Electrospray Ionization Tandem Mass Spectrometry†. Journal of the American Chemical Society 1996, 118, (2), 451-457. 18. DeLong, C. J.; Baker, P. R.; Samuel, M.; Cui, Z.; Thomas, M. J., Molecular species composition of rat liver phospholipids by ESI-MS/MS: the effect of chromatography. J Lipid Res 2001, 42, (12), 1959-68. 19. Zhang, X.; Reid, G. E., Multistage tandem mass spectrometry of anionic phosphatidylcholine lipid adducts reveals novel dissociation pathways. International Journal of Mass Spectrometry 2006, 252, (3), 242-255. 20. Frega, N. G.; Pacetti, D.; Boselli, E., Characterization of Phospholipid Molecular Species by Means of HPLC-Tandem Mass Spectrometry, Tandem Mass Spectrometry Applications and Principles. In Tandem mass spectrometry applications and principles, Prasain, J., Ed. InTech: 2012. 21. Bujak, R.; García-Álvarez, A.; Rupérez, F. J.; Nuño-Ayala, M.; García, A.; RuizCabello, J.; Fuster, V.; Ibáñez, B.; Barbas, C., Metabolomics Reveals Metabolite Changes in Acute Pulmonary Embolism. Journal of Proteome Research 2013, 13, (2), 805-816. 22. Ciborowski, M.; Zbucka-Kretowska, M.; Bomba-Opon, D.; Wielgos, M.; BrawuraBiskupski-Samaha, R.; Pierzynski, P.; Szmitkowski, M.; Wolczynski, S.; Lipinska, D.; Citko, A.; Bauer, W.; Gorska, M.; Kretowski, A., Potential first trimester metabolomic biomarkers of abnormal birth weight in healthy pregnancies. Prenat Diagn 2014, 34, (9), 870-7. 23. Jackson, S. N.; Wang, H. Y.; Woods, A. S., In situ structural characterization of phosphatidylcholines in brain tissue using MALDI-MS/MS. J Am Soc Mass Spectrom 2005, 16, (12), 2052-6. 24. Chughtai, K.; Jiang, L.; Greenwood, T. R.; Glunde, K.; Heeren, R. M., Mass spectrometry images acylcarnitines, phosphatidylcholines, and sphingomyelin in MDA-MB231 breast tumor models. J Lipid Res 2013, 54, (2), 333-44. 25. Zabrouskov, V.; Al-Saad, K. A.; Siems, W. F.; Hill, H. H.; Knowles, N. R., Analysis of plant phosphatidylcholines by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Rapid Commun Mass Spectrom 2001, 15, (12), 935-40. 26. Domingues, P.; Amado, F. M. L.; Santana-Marques, M. G. O.; Ferrer-Correia, A. J., Constant neutral loss scanning for the characterization of glycerol phosphatidylcholine phospholipids. Journal of the American Society for Mass Spectrometry 1998, 9, (11), 11891195. 27. Volmer, D. A.; Lock, C. M., Electrospray ionization and collision-induced dissociation of antibiotic polyether ionophores. Rapid Commun Mass Spectrom 1998, 12, (4), 157-64.

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TABLES Table 1: Summary of characteristic and diagnostic fragments for PC, PE, SM and different adducts recognition, both in positive and negative ionisation mode.

PC

PE

SM

Positive mode

Negative mode

Recognition of PC fragment of m/z 184.0733 – protonated phosphocholine fragment of m/z125.0009 – protonated phosphate loss of m/z 183.0733 – phosphocholine Recognition of sodiated PC fragment of m/z 146.9817 – sodiated phosphate loss of m/z 205.0479 – phosphocholine with sodium Recognition of potassiated PC fragment of m/z 162.9557 – potassiated phosphocholine loss of m/z 221.0219 – phosphocholine with potassium Recognition of sodium formate cluster loss of m/z 67.9874 – sodium formate loss of m/z 127.0596 – trimethylamine with sodium formate loss of m/z 251.0537 – phosphocholine with sodium formate loss of m/z 273.0366 - phosphocholine with sodium and sodium formate Recognition of other adduct than hydrogen fragment of m/z 146.9817 – sodiated phosphate loss of m/z 59.0734 – trimethylamine neutral losses with high abundance Recognition of PE fragment of m/z 164.0083 – sodiatedphosphoethanolamine loss of m/z 141.0191 – phosphoethanolamine loss of m/z 43.0340 – vinylamine Recognition of sodiated PE fragment of m/z 120.9660 – sodiated phosphoric acid loss of m/z 59.0371 – acetamide loss of m/z 164.0010 – phosphoethanolamine with sodium

Recognition of PC fragment m/z 168.0358 – deprotonated demethylated phosphocholine fragment m/z 224.0693 – demethylated phosphocholine dehydrated glycerol ester loss of m/z 242.0798 – demethylated phosphocholine glycerol ester Recognition of PC with formate attachment loss of m/z 60.0222 – methyl formate Recognition of PC with chloride attachment loss of m/z 49.9926 – methylated chloride Determination of fatty acyls composition fatty acids signal – [FA – H]lyso-form signal – [LPC – CH3][LPC – CH3 – H2O]-

Recognition of SM fragment of m/z 184.0733 – protonated phosphocholine Recognition of sodiated SM fragment of m/z 146.9817 – sodiated phosphate loss of m/z 205.0479 – sodiated phosphocholine Recognition of potassiated SM fragment of m/z 162.9557 – potassiated phosphocholine loss of m/z 221.0219 – potassiated phosphocholine Recognition of other adduct than hydrogen loss of m/z 59.0734 – trimethylamine neutral losses with high abundance

Recognition of deprotonated PE fragment m/z 140.0118 – deprotonated phosphoethanolamine fragment m/z 196.0380 – deprotonated doubly dehydrated glycerol-phosphocholine Recognition of PE with formate attachment fragment m/z 168.0431 – deprotonated ethanol-ethylamine phosphate loss of m/z 60.0222 – methyl formate Recognition sodium formate cluster loss of m/z 67.9874 – sodium formate Determination of fatty acyls composition fatty acids signal – [FA – H]lyso-form signal – [LPE – H][LPE – H – H2O]Recognition of SM fragment m/z 168.0358 – deprotonated demethylated phosphocholine Recognition of SM with formate attachment loss of m/z 60.0222 – methyl formate Recognition of SM with chloride attachment loss of m/z 49.9926 – methylated chloride

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FIGURES

Figure 1: Schematic representation of phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and sphingomyelines (SMs). Blue boxes highlight the head groups.

Figure 2: An example of multi-adducts ionisation. The example shown corresponds to the sphingomyelin SM(d18:1/16:0). A) Extracted Ion Chromatogram (EIC) for SM ionised in positive ionisation mode with three different adducts: [M+H]+, [M+Na]+ and [M+K]+; B) Mass spectrum with ions corresponding to the three different adducts: [M+H]+, [M+Na]+ and [M+K]+ of SM; C) Extracted Ion Chromatogram (EIC) for SM ionised in negative ionisation mode with two different adducts: [M+HCOO]- and [M+Cl]-; D) Mass spectrum with ions corresponding to two different adducts: [M+HCOO]- and [M+Cl]- of SM. 21

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Figure 3: Representative positive ion ESI CID mass spectra for phosphatidylcholine PC(20:5/16:0): A) PC ionised with hydrogen [M+H]+; B) PC ionised with sodium [M+Na]+;

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C) PC ionised with potassium [M+K]+; D) PC ionised with hydrogen and with sodium formate cluster [M+H.HCOONa]+.

Figure 4: Representative negative ion ESI CID mass spectra for phosphatidylcholine PC (16:0/18:2): A) PC ionised with formate [M+HCOO]-; B) PC ionised with chloride [M+Cl]-.

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Figure 5: Representative positive ion ESI CID mass spectra: A) PE(16:0/20:4) ionised with hydrogen [M+H]+; B) PE(16:0/18:2) ionised with sodium [M+Na]+.

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Figure 6: Representative negative ion ESI CID mass spectra for phosphatidylethanolamine: A) PE(16:0/18:2) ionised by deprotonation [M-H]-; B) PE(18:1/16:1) ionised with formate [M+HCOO]-; C) PE(16:0/18:2) ionised by deprotonation with sodium formate cluster [MH.HCOONa]-.

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Figure 7: Representative positive ion ESI CID mass spectra for sphingomyelin SM(d18:1/16:0): A) SM ionised with hydrogen [M+H]+; B) SM ionised with sodium [M+Na]+; C) SM ionised with potassium [M+K]+;

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Figure 8: Representative negative ion ESI CID mass spectra for sphingomyelin SM(d18:1/16:0): A) SM ionised with formate [M+HCOO]-; B) SM ionised with chloride [M+Cl]-.

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GRAPHICAL ABSTRACT

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