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The Caenorhabditis elegans lipidome A primer for lipid analysis in Caenorhabditis elegans Michael Witting a,⇑, Philippe Schmitt-Kopplin a,b a Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany b Lehrstuhl für Analytische Lebensmittelchemie, Technische Universtität München, Wissenschaftszentrum Weihenstephan, Alte Akademie 10, 85354 Freising-Weihenstephan, Germany

a r t i c l e

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Article history: Received 14 April 2015 and in revised form 2 June 2015 Available online xxxx Keywords: Lipidomics Caenorhabditis elegans Lipid analysis Model organism

a b s t r a c t Lipids play important roles in biology, ranging from building blocks of membranes to signaling lipids. The nematode and model organism Caenorhabditis elegans has been used to explore lipid metabolism and several techniques for their analysis have been employed. These techniques include different possibilities ranging from visualization of lipid droplets, analysis of total fatty acids to analysis of complex lipids using lipidomics approaches. Lipidomics evolved from metabolomics, the latest off-spring of the ‘‘omics’’-technologies and aims to characterize the lipid content of a given organism or system. Although being an extensively studied model organism, only a few applications of lipidomics to C. elegans have been reported to far, but the number is steadily increasing with more applications expected in the near future. This review gives an overview on the C. elegans lipidome, lipid classes it contains and ways to analyze them. It serves as primer for scientists interested in studying lipids in this model organism and list methods used so far and what information can be derived from them. Lastly, challenges and future (methodological) research directions, together with new methods potentially useful for C. elegans lipid research are discussed. Ó 2015 Elsevier Inc. All rights reserved.

Introduction Lipidomics, the comprehensive analysis of lipids Lipids play essential roles cross all kingdoms in biology and their analysis in health and disease has a long tradition. In the post-genomic era more emphasis is put on functional analysis of genes and genomes using tools of functional genomics: transcriptomics, proteomics and metabolomics, all of them studying a different subpart of a cells or organisms interior. Because lipids play such an important role as building blocks of membranes, energy storage or second messengers and signal transducer, the comprehensive analysis of lipids evolved from metabolomics as individual discipline called ‘‘lipidomics’’. In contrast to general assumption that lipids represent a rather homogenous class, several tens of thousands different lipid structures are possible [1]. Lipids are present in a large diversity, from ubiquitous bulk phospholipids in the membranes to highly specific signaling lipids and span several orders of magnitude in concentration. Additionally, different lipid classes have large ⇑ Corresponding author. E-mail address: [email protected] (M. Witting).

differences in polarity (e.g. PC(18:0/16:0) has a log P of 11.94 and TG(16:0/16:0/16:0) a log P of 22.08) or molecular mass (e.g. palmitic acid: 255.231857, [MH]-compared to CL(10 -[18:2(9Z,12 Z)/18:2(9Z,12Z)],30 -[18:2(9Z,12Z)/18:2(9Z,12Z)]): 1447.964950, [MH]-), which dramatically complicates their analysis. Today, lipidomics is mainly based on Mass Spectrometry (MS), but also Nuclear Magnetic Resonance (NMR) has been employed [2]. Two different kinds of MS analysis can be differentiated: (i) shotgun lipidomics directly infuses raw lipid extracts into the MS and uses combinations of neutral loss and product ion scans to differentiate and identify lipids and is mostly carried out on ion trap MS offering MSn capabilities, but also Quadropole-Time of Fligth (Q-ToF) instruments are employed. Major advantage of this technology is its high-throughput possibility. However, missing separation of isomeric lipids is the major disadvantage of this approach. (ii) Lipid profiling using Liquid Chromatography–Mass Spectrometry (LC–MS) is the second most used technique so far. The use of chromatographic separation enables resolving of isomers including cis/trans isomers [3]. In most cases, reversed phase (RP) separations using C8 or C18 columns with an Acetonitrile-iso-Propanol (ACN-iPrOH) gradient are employed [3–5], but also application of HILIC and normal phase separation is common [6,7]. Lipidomics is applied in any field of biological 0003-9861/Ó 2015 Elsevier Inc. All rights reserved.

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research ranging from cell cultures [8], microorganisms [9–11], plants [12,13] and mammals [14]. Caenorhabditis elegans, a versatile model organism The soil-dwelling nematode C. elegans has become a major model organism in biology. It offers several experimental advantages, including a fast reproductive cycle, a translucent body, known cell lineage and a sequenced genome, which was the first of a multicellular organism [15]. Furthermore, its hermaphroditic nature allows raising a large number of isogenic animals in short time. The full developmental cycle of C. elegans from eggs to fertile adults takes about 3 days at 20 °C. The worm develops through four larval stages, named L1 to L4. Under unfavorable conditions, like overcrowding or food scarcity it can enter an alternative, non-feeding and long-lived, developmental stage, the dauer stage (dauer, german for enduring). After conditions ameliorate dauer larvae normally develop through L4 larvae to adults without compromises in adult life span. C. elegans is used as model organism in different research fields (e.g. toxicology, developmental biology, neurobiology, hostpathogen interactions, aging research and others). A large array of tools was developed over the past years involving automated worm-sorting, micro arrays for transcriptomics, imaging technologies, transgenics or tissue specific gene inactivation [16]. Further details on the biology of the worm can be found in the review by Hulme and Whitesides [17]. Although extensively studied, metabolomics and lipidomics investigations on C. elegans are scarce, but number of publications related to this topic is increasing steadily. Within in this review we aim to give a general overview on lipids present C. elegans. This information was inferred from genetic information on lipid metabolism readily available since many years and results from different publication. From this we deduced lipid classes and species that might be present in the worm. Furthermore, we introduce methods for their analysis and how they have been used so for analysis of the C. elegans lipid content. Finally, challenges and needs for successful, future lipidomic investigations are discussed. This review serves as primer for scientists interested in analyzing lipids in the model organism C. elegans. The C. elegans lipidome C. elegans is able to produce a wealth of different lipids. In 2013 Zhang et al. collected ‘‘all’’ lipid metabolic genes present in the worm by comparative genomics. In total they found 471 lipid genes curated from KEGG, literature research and orthologues of human lipid genes. 237 of 471 of these genes are conserved in humans, mice, rats or Drosophila. More specifically 71 of these conserved genes are related to human metabolic diseases. Using the OMIM database most genes were annotated by the keywords ‘‘Obesity, Diabetes, Metabolic disease and others’’. Furthermore, 327 genes in C. elegans are orthologues to human disease genes, which implies that lipid genes are also involved in diseases different from metabolic syndrome. This collection was complemented by a functional study using RNA interference (RNAi), which revealed several phenotypes, including growth and developmental defects also for genes not reported so far [18]. One particular example how such genes relate to human disease genes was published by Hashmi et al., who used the worm’s intestine as model system to study the role of Krüppel-like factors in fat regulation, cell death and phagocytosis [19]. Additional the role of these factors in human metabolic regulation was reviewed and KLF-3 for example acts selectively on insulin components [20].

Although of impressive nature, this work and other genetic studies gives no information on the actual chemical diversity of the lipid content, which is very strongly condition dependent (e.g. availability of building blocks like fatty acids). In this part we present different lipid classes found in C. elegans, their biosynthetic pathways and selected biological actions. Table 1 summarizes classes present in the worm along with their commonly used abbreviations and LipidMaps identifiers, while Fig. 1 shows their basic structure examples of them. Fatty acids and amides Except for steroids, fatty acids are one of the major building blocks of complex lipids. C. elegans is able to synthesize a broad variety of fatty acids on its own, including saturated (FA), monoand polyunsaturated (MUFA and PUFA) and mono methyl branched fatty acids (mmBCFA). Straight chain fatty acids are synthesized from acetyl-CoA as primer by condensation with malonyl-CoA in contrast to mmBCFAs, which are produced from branched chain primers derived from catabolism of branched chain amino acids. Fatty acids biosynthesis has been extensively studied and several elongases and desaturases and their regulation have been described [21,22]. A 13C isotope labeling approach demonstrated which fatty acids are directly taken up from the worm’s diet and which are synthesized de novo. The two cyclo propane fatty acid C17D and C19D are exclusively taken up from bacterial diet and C16:1n7 and C18:1n7 are synthesized de novo in minor amounts of about 5%, whereas C16:0, C18:0, C18:1n9, C18:2n6 are produced in increasing amounts ranging from 7.2% to 19% and mmBCFAs are exclusively synthesized de novo [23,24]. Fatty acids not only serve as building blocks for higher lipids, but have rather important biological roles. For example c-linolenic and stearidonic acid are required for basal immunity during infection with Pseudomonas aeruginosa [25], while oleic acid and NHR-80/HNF4 are needed for longevity in germline ablated worms [26]. The mmBCFA C17:0iso is essential for postembryonic growth of L1 larvae [27]. Additionally, C17:0iso and ACS-1 are shown to be needed for inositol triphosphate (IP3) signaling for early embryonal development [28]. Furthermore, it has been demonstrated that PUFAs are important for correct neurotransmission in C. elegans. Watts et al. encountered non-normal behavior of fat-3 mutants during their studies of fatty acid metabolism [29]. Depletion of PUFAs in fat-3 mutants leads to movement deficiencies, inability to respond to head-touch and egg laying defects similar to egl-1 mutants. Defects in motility were rescued by arachidonic acid (C20:4n-6) and docosahexaeonic acid (C22:6n-3), similarly expression of fat-3 under control of the neuronal promotor unc-119 could also rescued the egl phenotype. Further experiments lead to the conclusion that mutation of fat-3 leads to functional but not developmental defects in the nervous system and insufficient neurotransmitter release [30]. Composition of fatty acids also correlates with longevity. Fatty acid profiles from different long lived mutants were measured and by correlating relative longevity with different parameters (e.g. chain length or degree of unsaturation) different trends became apparent. First, the amount of MUFAs increases, while PUFAs decrease with longevity. In parallel a trend towards shorter chain length is observed. Results were also in accordance with susceptibility to hydrogen peroxide [31]. One lipid class directly derived from fatty acids are fatty amides, represented in C. elegans by N-acylethanolamides (NEA). This lipid class includes the mammalian endocannabinoid anandamide and is synthesized by acylation of the ethanolamine nitrogen of PEs followed by cleavage of the phosphate ester bond yielding a NEA and phosphatidic acid. Eicosapentanoyl ethanolamide is reduced upon starvation or dietary restriction and mediates diet effects to

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M. Witting, P. Schmitt-Kopplin / Archives of Biochemistry and Biophysics xxx (2015) xxx–xxx Table 1 Lipid classes present in C. elegans inferred from genetic information.

Lipid class





Sphingosine Sphiganine (Dihydrosphingosine) Sphingosine 1-phosphate Sphinganine 1-phospate N-Acylsphingosine (Ceramide) N-Acylsphinganine (Dihydroceramide) Ceramide 1-phosphate Sphingomyelin Glucosylceramide Lactoyslceramide


CerP SM GlcCer LacCer

SP0101 SP0102 SP0105 SP0105 SP0201 SP0202 SP0205 SP0301 SP0501 SP0501


1-Acyl-sn-glycerol 1,2-Diacyl-sn-glycerol Triacylglycerol


GL01 GL02 GL03


Phosphatidic acid Phosphatidylcholine Phosphatidylserine Phosphatidylethanolamine Phosphatidylmonomethylethanolamine Phosphatidyldimethylethanolamine Phosphatidylinositol Cardiolipin


GP10 GP01 GP03 GP02 – – GP06 GP12

Steroids and related substances

Steroids Dafachronic acids Cholesterylester


ST0101 ST0403 ST0102




Fatty acids

Straight chain fatty acids Branched chain fatty acids Unsaturated fatty acids


FA0101 FA0102 FA0103

Fatty amides Prenol lipids

Fatty amides Isoprenoids Quinonnes


FA0804 PR01 PR02




S1P Cer

Depicted class also includes fatty acids bound as alkyl or alkenyl.

lifespan [32]. In a metabolomics approach oleolyethanolamide was identified to be increased in long lived worms over expressing lipl-4, and binds to the proteins LBP-8 and NHR-80, activates target genes of NHR-80 and NHR-49 and promotes longevity [33].

Glycerophospholipids Glycerophospholipids, as building blocks of membranes, represent the largest portion of the lipidome. Chemically they are built from two fatty acids esterified to the sn1 and sn2 positions of glycerol and different head groups attached to sn3 position. Additionally, side chains at the sn1 position can be bound by either an acyl, alkyl or alkenyl bond. Generally fatty acids bound on the sn1 position have a low degree of unsaturation, while different fatty acids can be found on the sn2 position. From genetic analysis C. elegans is able to synthesize and use a high diversity of different head groups, resulting in many different lipid classes: phosphatidic acids (PA), phosphatidyl cholines (PC), phosphatidyl ethanolamines (PE), phosphatidyl serines (PS), phosphatidyl glycerols and glycerol phosphates (PG and PGP), and phosphatidyl inositols (PI). Furthermore, cardiolipins (CL) are found in mitochondrial membranes and N-mono- and di-methyl phosphatidyl ethanolamines (MMPE and DMPE) are intermediates in the synthesis of PCs from PEs present in certain mutants or knock-downs [34]. For the three major glycerophospholipid classes (PC, PE and PS) biosynthesis pathways are strongly connected (Fig. 2B). PCs can be synthesized on different routes. First, the Kennedy pathway (blue in Fig. 2B) uses dietary choline or phosphoryl choline derived from the phosphobase methylation pathway [34,35] (red in Fig. 2B) and its activated form CDP choline for coupling to diacylglycerols

(DG). There is some evidence for the existence of the Bremer– Greenberg pathway in C. elegans [36]. PS synthesized from PC by exchange of the choline head group with serine catalyzed by PSSY-1 [37] and PE is derived from PS by decarboxylation. As major building blocks of membranes, glycerophospholipid strongly influence mechanical properties of cells and membrane fluidity. In the previous paragraph PUFAs were linked to correct neurotransmission. Newer work shows that PUFAs bound to specific glycerophospholipids are needed for neuronal cell mechanics and touch sensation. fat-3, fat-4, fat-1 and elo-1 had reduced touch response compared to wild type worms. Mutants were supplemented with either arachidonic acid (C20:4n-6), eicosopentaenoic acid (C20:5n-3) or both. Interestingly, only when both were supplied mutants behaved like the wild type and in the next step it was evaluated if PUFAs bound to phospholipids or in another form are needed for phenotypic rescue. The enzymes MBOA-7 and MBOA-6 are responsible for integrating PUFAs into PIs or PCs, PEs and PSs. mboa-7 mutants and mboa-6(RNAi) (knockout of mboa-6 is lethal) were fed either with PE(18:0/20:4), PC(18:0/20:4) or PS(18:0/20:4) or different combinations. Only PE(18:0/20:4) and PS(18:0/20:4) showed significant enhancement. Lastly, isolated touch receptor neurons (TRNs) of wild type and fat-1; fat-4 animals showed different membrane mechanics [38].

Sphingolipids Sphingolipids play important roles as both structural units and signaling molecules. Structurally, they are built from a sphingoid base, derived from condensation of a fatty acid (usually C16:0) with serine and N-linked fatty acid. C. elegans on the contrary uses

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Fig. 1. Structures of lipid classes present in C. elegans (A) sphingolipids usually contain a C17iso sphingoid base. Different derivatives are possible, including S1P, Cer, CerP, SM, GlcCer and LacCer, (B) Glycerolipids are the major energy storage in C. elegans. MG and DG also serve as precursor for other lipids. (C) Glycerophospholipids are the major lipid class found as building blocks of biological membranes in high amounts. C. elegans is capable of synthesizing a wide range with different headgroups, e.g. PA, PC, PS, PE, MMPE, DMPE and PI. (D) The bile acid like dafachronic acids (D7-DA shown as example) are important signaling molecules in development and nematodal longevity. (E) Maradolipids are special lipids found in dauer larvae, only recently discovered (F) Fatty acids are used as building blocks of complex lipids, but also serve as signaling molecules, while fatty amides are important signaling molecules, e.g. linking food to lifespan.

C15:0 and produces a C17:0iso branched chain sphinganine base (d17:0iso-SPA). However under certain conditions, like RNAi of the gene let-767, glucosylceramides also contain C16 and hydroxy-C17:0 iso sphingoid bases [39]. Interestingly, N-linked fatty acid side chains contain 2-hydroxy fatty acids, mostly C22:0-OH [40]. The biosynthesis pathway with all related genes is shown in Fig. 2C. Previous work showed that elo-5 loss-of-function mutations lead to arrest in the early L1 stage. Zhu et al. demonstrated that this mutation leads to disruption of a novel sphingolipid-TORC1 pathway needed for normal development. Several genes for synthesis of glucosyl ceramides (GlcCer) from d17:iso-SPA were tested and exogenous supplementation with specific sphingolipids could rescued the phenotype of elo-5() and splt-1(RNAi), but not of fath-1(RNAi) and cgt-1(), cgt-3() (fath-1 encodes for fatty acid 2-hydroxylase and cgt-1 and cgt-3 for ceramide glucosyl transferases), which suggests that d17iso-GlcCer is the mediator in this pathway. Using a genetic screen a loss-of-function mutation of nprl-3 was detected to abolish this effect [41]. These results directly link mmBCFA to a new signaling pathway. Other publications demonstrated that ceramides are required for anoxia

protection [42], autophagy dependent life span extension [43] or radiation induced apoptosis [44]. Glycerolipids Excessive energy in C. elegans is stored in form of lipid droplets, containing tri acyl glycerols (TGs), which are primarily located in epidermal and intestinal cells (up to 35% of body dry mass) and to a lesser extends in form of glycogen (3.3% of body dry mass). Lipid storage vesicles are not overlapping with lysosome-related organelles [45]. For mobilization of energy from these resources the worm harbors several lipases, some also linked to longevity. lipl-4 for example is needed for induction of autophagy and is also required for life span extension in germ line ablated animals [46]. Similarly, also diacylglycerol lipases regulate lifespan [47]. Fat storages are mobilized during starvation, for example dauer larvae accumulate fat storages, which are utilized during prolonged starvation [48,49]. The full complement of peroxisomal and b-oxidation genes is present in C. elegans for generation of energy from fat storages, including a functional methylmalonyl-CoA epimerase for degradation of mmBCFAs [50,51].

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Fig. 2. Examples of different lipid synthesis pathway present in C. elegans. Genes encoding lipid enzymes are depicted in red next to the reaction the products catalyze. (A) A vast amount of different fatty acids with different chain length and degree of saturation can be produced by C. elegans on its own, although it utilizes fatty acids derived from bacterial diet directly. Exceptions are mmBCFA, which are almost exclusively synthesized by the worm itself. (B) Glycerophospholipids are the major building blocks of biological membranes and the synthesis of different classes is strongly interwoven. The shaded orange region shows the phosphobase methylation pathway producing phosphoryl choline from serine. The Kennedy pathway (blue region) directly utilizes dietary choline for synthesis of PC. Lastly, PS is produced from PC by exchanging the headgroups. Some evidence for existence of the Bremer–Greenberg pathway (green region) has been found in C. elegans.

Steroids and related substances The worm is a sterol auxotroph and therefore sterols have to be supplied exogenously by the diet, whereby different sterols can serve the needs of C. elegans. Interestingly, the needed amount of sterols is too low to have structural roles, but is rather needed for synthesis of steroid signaling molecules [52]. Indeed, development is regulated by bile acid like steroid hormones called dafachronic acids [53]. Several different forms of dafachronic acid have been identified [53,54], but the exact biosynthesis pathway is still not completely known. Dafachronic acids not only regulate development, but are also required for signaling in longevity. For example the long life of germline ablated animals involves the

presence of the DAF-9/DA/DAF-12 pathway [55–57]. Furthermore, dietary restriction mediated longevity also relies on dafachronic acid signaling, but instead of DAF-12 its close homolog NHR-8 is required and let-363/mTOR is essential for this mediation [58]. Beside this bile acid like steroid hormones C. elegans contains different other sterols, where by the actual content of individual compounds is dependent on the sterol supplementation [59,60]. Glycolipids A special class of glycolipids was recently discovered in dauer larvae of C. elegans: 6,60 -diacyltrehaloses, called maradolipids. Interestingly most of the detected lipids from this class contained

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at least one mmBCFA side chain. Further experiments showed that these special lipids are part of the dauer body structural unit, the microvilli in the lumen. Using elo-5 RNAi in a daf-2 background or the daf-2;DDtps mutant microvilli size is reduced or completely missing [61]. Prenol lipids Prenol lipids are derived from Acetyl-CoA utilized in the mevalonate pathway. In contrast to other animals, C. elegans lacks the cholesterol producing branch of the mevalonate pathway, but all others are highly conserved. This makes the worm an ideal model organism for the study of the non-cholesterol producing branches. Knockdown of any enzyme of the main branch producing Franesyl-PP from Acetyl-CoA leads to embryonic lethality. Likewise, inhibition of HMG-CoA reductase by statins also leads to embryonic lethality [62]. Important functions of prenol lipids are derivatization of adenosine in tRNAs for stabilization of codon–anticodon interactions [63], production of coenzyme Q (although also supplied by bacterial diet) [64] or protein modification [65]. For further information on the mevalonate pathway in C. elegans refer to the review by Rauthan and Pilon [66]. Others classes Ascarosides are a special class of lipid derived molecules, which have different functions, from dauer inducing pheromone (daumone) [67], male attractants [68] to signaling of aggregation [69]. Ascaroside signaling integrates building blocks from fatty acid, amino acid metabolic and other pathways to form a modular library of pheromones [70,71]. Peroxisomal b-oxidation is important for synthesis of ascarosides and requires daf-22 and dhs-28 for production of short chain fatty acids from very long chain fatty acid precursors. More recently mutation in the acyl-CoA oxidases acox-1, -2 and -3 has been shown to lead to defects in ascaroside signaling [72]. More information on this special class can be found in the recent review of Frank Schröder [71].

Applied lipids analysis methods C. elegans produces a vast amount of lipids covering a large combinatorial and chemical space and the question rises how this diversity can be accessed analytically? In the same way as lipids also methods for their analysis are very diverse, ranging from imaging methods, analysis of single classes (e.g. fatty acid analysis with GC) or profiling of the (complete) lipid content using MS based technologies. Plenty of work has been carried out on the level of fatty acids. However, as examples above have shown not only composition of fatty acids but also their origin or relation to complex lipids is important. Comprehensive analysis of intact lipids only recently joined the C. elegans toolbox. Still, several analytical chemistry methods have been used, on which the current technology is built on. Major analysis technologies are imaging of lipid deposits in C. elegans using fluorescent dyes or other technologies, analysis of lipid fractions with TLC and analysis of fatty acid composition with GC and GC–MS. However, the two new MS based technologies, shotgun lipidomics and LC–MS based lipid profiling, are catching up. Depending on the nature of the biological question that needs to be answered different approaches or technologies might be selected. The following paragraphs gives an overview on methods employed with C. elegans so far and compares their advantages and disadvantages. Fig. 3 shows a flow chart with different possibilities for analysis of lipids and Table 2 compares their advantages and disadvantages.

Tools for imaging of lipids and lipid deposits in C. elegans Classically, lipid deposits are labeled with fluorescent dyes that concentrate in hydrophobic environments. The phenoxazone dye Nile red or BODIPY labeled fatty acids are used for imaging of lipid deposits in cell lines or C. elegans, by mixing with the worm’s diet [73,74]. However, broader analysis indicated that these dyes do not label major fat storages in C. elegans, instead fixation and staining with oil red O correlated well with biochemical analysis of lipid content [45]. Imaging in live animals is a useful tool to follow

Fig. 3. Different possibilities for analysis of lipids and lipid deposits in C. elegans have been described. This flow chart shows all major techniques and approaches with example literature. Different combinations of steps can be employed to reach an optimal result, e.g. extraction, fraction and measurement of a specific class or fraction.

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Table 2 Summary of advantages, disadvantages and information content of different technologies for analysis of C. elegans lipids. Method



Information content

Imaging (e.g. Fluorescence labeling, SRS CARS)

 Direct analysis  Non-invasive, live imaging possible (CARS, SRS)

 No information on lipid composition  For analysis of specific lipids or tracers with tags are needed

 Localization and amount of labeled and/or detectable lipids


 No special equipment needed  Fast, easy and cheap

 Only limited information

 Amount of lipid classes


 High resolution separation of isomers  Absolute quantification of different fatty acids

 Only amenable to volatile lipids or lipids that can be made volatile by derivatization

 Fatty acid composition  Amount of isomeric fatty acids

Shotgun lipidomics

 Fast, high-throughput capable (analysis time of several minutes)  Absolute quantification possible

 No separation of isomers

 (absolute) quantities of different lipids


 Separation of isomeric molecules  Absolute quantification possible

 Long analysis time, typically between 15 to 25 min

 Absolute or relative quantities of different lipids, also for (chromatographically) separable isomers


 Ultrahigh resolution allows separation of isobaric molecules  Fast and high throughput capable

 No differentiation between isomeric molecules

 Relative quantification of isobaric lipids  Exact mass and molecular formula for unknown lipids

individuals over time. Choline containing metabolites and lipid were imaged in live C. elegans using Stimulated Raman Scattering (SRS) together with isotope-based metabolic labeling, that shifted the N–H (N–D) bond vibration to 2100 cm1 in the cell silent Raman window [75]. Similarly, alkyne-tagged small biomolecules have been used in conjunction with SRS for live-cell imaging, including C. elegans. 5-Ethynyl-20 -deoxyuridine, 5-Ethynyl uridine, L-Homopropargylglycine,

Propargylcholine and 17-Octadecynoic acid were used to follow de novo synthesis of DNA, RNA, proteins, phospholipids or triacylglycerols respectively [76]. Another example made use of SRS together with phenyl-diyne cholesterol, which is stable and permits specific detection, to investigate cholesterol storage in wild type worms and chup-1 mutants, which are deficient in cholesterol uptake [77]. Though for these methods labels are needed, whereas coherent anti-Stokes Raman scattering (CARS) is not dependent on prior labeling. CARS was compared with different fat labeling methods under different conditions, which revealed that CARS is the method of choice, if available [78]. Several other studies reported to use of CARS as label-free approach to follow lipid metabolism in C. elegans [79–81]. However, all these methods give only very unspecific information on total lipid classes, but not on individual lipid species. MS based imaging is interesting alternative for metabolite and lipid imaging directly in tissues without the necessity of prior labeling. Matrix Assisted Laser Desorption Ionization–Mass Spectrometry (MALDI–MS) and Time of Flight-Secondary Ion Mass Spectrometry (ToF-SIMS) based techniques have been used with C. elegans in two proof-of-principle publications [82,83]. For routine application of this technology several developments have to be made, especially spatial resolution in MALDI–MS has to be in an acceptable range to visualize different tissues (see also Challenges and Future research directions).

Lipid extraction and fractionation If individual lipids or lipid classes have to be analyzed they need to be extracted from a C. elegans sample. The two most employed lipid extraction methods are the Folch [84] and Bligh and Dyer protocols [85]. Both extraction protocols are based on chloroform/methanol, yet often replaced with protocols using MTBE [86,87], due to the carcinogenic nature of chloroform and environmental concerns. Comparison of extraction protocols, in which also

C. elegans eggs were included as one particular sample, exhibited that the new method has similar yields. In contrast to chloroform, MTBE based extractions build a two phase system with the organic solvent on the top and cell debris on the bottom particularly useful for robotic automation [86]. Lipid composition of C. elegans can be assessed on class level in the simplest way by the use of thin layer chromatography (TLC). This method is easy to use and no specialized equipment is needed and can be performed analytically or preparative for isolation of specific lipid classes. Quantification is achieved by general or specific staining (e.g. glycolipids [61] or phospholipids [88]) and densitometry. Use of 2D-TLC, adding a second separation dimension, increases resolution of this technique [61]. Solid phase extraction (SPE) represents an alternative for lipid fractionation and is mostly based on NH2 phases for separation of different lipid classes [88]. Also more advance materials for isolation of specific lipid classes (e.g. S1P) are available [89]. Information on lipid composition from these methods is limited, but they are useful for enrichment of specific lipid classes and can be combined with more sensitive and specialized methods, like GC–MS or shotgun lipidomics.

Mass spectrometry based methods Mass spectrometry is a powerful tool to decipher between different lipid species and allows precise relative and/or absolute quantification. It can be either used without (shotgun) or with chromatographic separation. Based on the nature of chromatography different lipids can be analyzed. GC and GC–MS is the most employed techniques for fatty acid analysis in C. elegans. Fatty acids are transferred to volatile methyl esters by esterification of free or trans-esterification of bound fatty acids. MS can be used in conjunction with isotopic labeling to determine rate of de novo synthesis [23]. GC–MS is often employed in conjunction with a prior fractionation using either TLC or SPE to assess the fatty acid composition of specific fractions. Despite, information on specific fatty acid combinations in complex lipids is lost. Results are usually expressed as percentages of detected fatty acids. GC allows high resolution separations, including baseline separation of iso and ante-iso fatty acids or different double bond isomers. A major problem when analyzing fatty acids with GC–MS is in source fragmentation of PUFAs under EI conditions.

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Using chemical ionization can overcome this and also allows locating double bonds in PUFAs [90,91]. A novel LC-MS based method might replace this approach in future, offering higher sensitivity using a charge reversal derivatization of free fatty acids with N-(4-aminomethylphenyl)pyridinium, although not applied to C. elegans yet [92]. The analysis of the fatty acid composition of intact lipids is getting more important, because there is only weak correlation between bound and free fatty acids. Liquid based techniques offer the possibility to introduce intact lipids into the MS. Two different approaches can be used. First, shotgun lipidomics directly infuses the raw lipid extract without prior chromatographic separation and analysis is performed on tandem mass spectrometers utilizing multiple neutral losses and product ion scans to determine lipid composition of different signals. Up to know this is the mostly employed analysis method for C. elegans lipidomes. Shotgun lipidomics in conjunction with multiple precursor and neutral loss scans and data dependent acquisition (DDA) was used for the analysis of the C. elegans lipidome. It was demonstrated that using this technique accurate identification and quantification can be performed in one single direct infusion experiment. The experiment was carried out on a Q-ToF experiment equipped with an automated nanospray chip ESI source (NanoMate) allowing long spraying times with a minimal consumption of sample extract. Phospholipids were extracted according to Bligh and Dyer and TAGs were isolated by 2D-TLC as described by Matyash et al. [93]. Limits of quantification (LOQ) in the lower nM range were achieved. In total 90 glycerophospholipids and 35 TGs with unique molecular formulae were detected in a single experiment. MS/MS data indicated that behind each individual molecular composition of one TG mass, 5 to 15 isobaric species can be found. Using systems of linear equations relative abundances of each specific isobar could be calculated [94]. The same group used multivariate analysis of high-resolution survey MS scans for lipidomics screening on an Orbitrap instrument similarly equipped with a NanoMate for long infusion times. For proof of concept RNAi of two genes, encoding putative methyl transferases, was conducted. Analysis showed presence of MMPE and DMPE in the corresponding extracts, proofing methyl transferase activity of the two genes called pmt-1 and pmt-2 [34]. Dedicated software tools in combination with shotgun lipidomics enables screening of novel lipids. The software LipidXplorer with its Molecular Fragmentation Query Language (MFQL) was used to specifically search for maradolipids in extracts from C. elegans dauer larvae in comparison to L3 larvae. Analysis revealed a novel class of lipids called lyso-maradolipids having only one fatty acid moiety specifically enriched in dauer larvae. Furthermore relative abundances of fatty acid side chains could be calculated for marado and lyso-maradolipids [95]. Due to missing chromatography direct infusion experiments benefit from employing high-resolution instrumentation. Ishida et al. performed direct infusion experiments using the NanoMate chip ESI source coupled to a Bruker APEX III ICR-FT/MS for analysis of C. elegans PEs. High-resolution of the employed MS differentiated between diacyl- and alkyl-acyl PEs solely on mass [96]. DI-ICR-FT/MS hold great promises for high throughput deep metabotyping [97] and will be potentially applied in future C. elegans lipidomics investigations. Several other studies likewise employed shotgun lipidomics [28,41–43]. The major drawback of shotgun lipidomics is the missing differentiation between isomeric lipids, for which reason chromatographic separation is needed. Traditionally normal-phase separations using silica columns and non-polar solvents for elution (e.g. iPrOH, hexane, chloroform, ethyl acetate or mixtures) have been used for analysis of lipid classes and was also employed to C. elegans [28]. However it requires dedicated equipment free of

water due to immiscibility of different organic solvents with water, which would lead bad chromatographic performance, unstable baselines and other problems. Hydrophilic Interaction Liquid Chromatography (HILIC) is an interesting alternative approach using water miscible organic solvents for lipid class separation [6,7]. The predominant method in lipidomics nowadays is based on RP separation and an ACN-iPrOH gradient, which allows detection of a broad range of different lipid classes and species within a single run [4]. Castro et al. for example studied the impact of daf-2 mutation on the metabolome and lipidome. For lipid analysis GC–MS for total fatty acids and LC-MS for intact lipids was utilized. LC-MS analysis was performed on a C8 column with an ACN-iPrOH gradient. Correlation analysis between total fatty acids and LC–MS data revealed a central role for C20:2 in lipid remodeling between triacylglycerol’s and phospholipids [98]. We have recently described a UPLC–MS based method for comprehensive analysis of the C. elegans lipidome using a sub-2 lm core shell particle C18 column. This method shows very high reproducibility as evaluated with lipid standard materials and C. elegans lipid extract, even between different column batches and days. Fig. 4 shows a typical chromatogram derived from this method. Use of DDA allows collection of MS/MS spectra of different lipids on a large scale already during profiling runs [5]. Furthermore, an automated approach for analysis of this large scale MS/MS data collection was developed. This novel approach, called LipidFrag, is based on the in silico fragmentation engine MetFrag. A classifier model based on true positive and false positive annotations of neutral precursor masses from MS/MS spectra of lipid standards was used to evaluate performance and calculation of reliability of in silico fragmentation results. Using this novel workflow ambiguous result can be filtered out [Witting et al., unpublished]. Challenges and future research directions Although only a limited number of investigations on comprehensive lipid analysis in C. elegans are published so far, much has been achieved. The worm as model system allows easy setup of experiments related to fat and lipid metabolism and storage and a lot of knowledge has been collected over the last years. Still, several lipid classes lack comprehensive measurements at the moment. Sphingosine kinases and lyases play important roles as shown by different studies [99], but comprehensive and reliable detection of their educts and products is still not achieved. Menuz et al., were able to detect C17iso sphingosine-1-phosphate and also found a 10-fold increase in sphk-1 mutants [42]. Potentially novel sample preparation methods can overcome this limitation, which also enabled detection new forms of S1P in Drosophila [89]. Lastly, direct detection and identification of intact lipids using either shotgun or LC–MS based lipidomics will replace long isolation, derivatization and measurement of fatty acids and will lead to new insights. However, several points have to be raised and should be addressed for successful future investigations. Dispatch the lack of C. elegans lipid standards The Metabolomics Standard Initiative (MSI) defined several levels of confidence for identification of metabolites and lipids, whereby the highest level (level 1) can be only achieved by comparison with an authentic standard under the same analytical conditions [100]. Such standards are not commercially available for certain lipids present in C. elegans. Especially for the maradolipids and several dafachronic acids no commercial standards are available. Though, synthesis protocols for both have been described [54,101–103]. Interestingly, ceramides with 2-OH-fatty acid are

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Fig. 4. Example chromatogram derived from a C. elegans lipid extract analyzed with the method from Witting et al. in positive ionization mode [5]. Three different clusters of lipid features can be detected. Detected classed referred in figure are independent of ionization mode.

available, but not with C17:0iso base. However, such standards would be needed for definite identification and comparison with ceramides present in C. elegans. Synthesis of chemical reference standards for each individual lipid is unrealistic and not feasible, but representative candidates from each lipid class are needed at minimum. Normally, lipids from the same class exhibit similar fragmentation spectra. Therefore one or several standards can serve as proxy for identification. Far more important is the need for suitable internal standards for normalization and quantification. Because C. elegans is capable of producing and using odd chain fatty acids, lipids normally applied as internals standards like PC(17:0/17:0) are not suitable. Isotopes labeled analogs are a possible solution (e.g. lipids with deuterated side chains or 13C labeled side chains) to this issue, but are either not available or very expensive. MALDI imaging to understand spatial distribution of lipids The nematode represents a multicellular organism with differentiated tissues. These tissues vary in their lipid content and composition. The intestine is the major storage of lipid droplets containing TGs. Similarly composition of phospholipids may vary between tissues. Several imaging tools have been described to locate and analyze lipid deposits, e.g. based on fluorescent dyes or CARS. These tools give no information on lipid composition, for example different fatty acid side chains or their combination. So far only phosphatidylcholine has been imaged using isotope labeling in combination with SRS [75]. MALDI–MS based imaging is gaining popularity as alternative tool to access lipid composition and spatial information in a single experiment. It is widely used in tissue analysis of proteins as alternative to classical histology. Application of metabolite imaging using MS in increasing with several areas of application [104], including lipid analysis [105]. MALDI–MS imaging to localize and visualize molecular information in the whole worm has been also described [82]. However, spatial resolution of available instruments is still insufficient for use with C. elegans. First results in our lab showed that metabolite imaging is theoretically possible,

but needs improvements in sample preparation and spatial resolution (unpublished). ToF-SIMS is an interesting alternative approach offering very high spatial resolution. An initial study used ToF-SIMS for analysis of C. elegans extracts, but also showed potential applicability in imaging of biomolecules [83]. Future developments towards higher spatial resolutions and increased sensitivity in MALDI–MS will open new fields in the analysis of C. elegans lipids.

Knowledge transfer and standardization Currently no centralized database for C. elegans lipid exists. The major database for lipidomics investigations is LipidMaps, containing near 40,000 unique lipid structures (status of 18.10.14) [106]. Still, major lipids present in C. elegans, e.g. ceramides with C17:0iso sphingoid bases or maradolipids are missing in this database. WormBase is the current gold standard for C. elegans biology and integration of metabolites, lipids and metabolic and lipid pathways would greatly facilitate dispersion of knowledge. One step in this direction was made with the creation of the SMID-DB, storing information on C. elegans signaling molecules [107]. Current efforts in our group are directed to generate a comprehensive in silico library of lipids potentially present in C. elegans, which can be validated and supplemented experimentally. A first step toward integration of C. elegans lipid data was done by the LipidMaps consortium by adding lipid related genes and proteins of C. elegans to the database. To make results from future lipidomics experiments in the worm comparable a standard lipid extract would be helpful. Similar efforts have been carried out to create a NIST standard ‘‘Metabolites in Human Plasma’’ [108]. Such a standard lipid extract could be run as additional quality control to validate results and allows comparison of different experiments. Potentially such a standard material can be produced for the different life stages and amount of specific lipids can be quantified and stored in an above mentioned database following the example of the Human Metabolome Database [109,110].

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Conclusion The nematode C. elegans is capable of synthesizing a large bunch of different lipids from fatty acids to glycerol- and glycerophospholipids, steroid hormones, glycolipids and many more. Different analytical methods have been employed to access this large chemical diversity. C. elegans is a proven model organism for lipid metabolism research. Lipids play a central role in the biology of the nematode, but also in other model organisms and are often linked intimately linked to reproduction and life span [111]. As shown lipids, e.g. ceramides in a novel TORC pathway, can serve as important signaling molecules. One might ask now based on this observation: How specific is the activity of this pathway? What lengths of the N-linked fatty acids are possible and do all of them act in the pathway or are just a few of the active and all other are produced transiently? The same questions can be asked for different lipid classes. With the advent of the descriptive ‘‘omics’’ technologies, including lipidomics these questions will be potentially answered. Furthermore, more and more lipid standards will become available allowing direct activity testing of them and facilitates lipid identification. A major advantage of C. elegans as model organism is that hypothesis can be tested in a straight forward manner with readily available mutants or feeding assays. Using RNAi, specific genes can be knocked down at specific time points without genetic mutation (knock-out), which makes it also possible to study function of genes of which a knock-out would be lethal during development. These possibilities have to be combined with novel tools and approaches already available or to be developed to fully exploit the potential of C. elegans. However, first steps into this direction are made. References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36]

G. van Meer, EMBO J. 24 (18) (2005) 3159–3165. H. Fernando et al., Alcohol. Clin. Exp. Res. 34 (11) (2010) 1937–1947. S.S. Bird et al., Anal. Chem. 84 (13) (2012) 5509–5517. C. Hu et al., J. Proteome Res. 7 (11) (2008) 4982–4991. M. Witting et al., J. Chromatogr. A 1359 (2014) 91–99. G. Boncompain et al., PLoS One 9 (1) (2014) e86196. M. Holcˇapek et al., J. Chromatogr. A 1377 (2015) 85–91. J. Li et al., Anal. Chem. 85 (9) (2013) 4651–4657. M. Jain et al., Proc. Natl. Acad. Sci. 104 (12) (2007) 5133–5138. D. Portevin et al., MicrobiologyOpen 3 (6) (2014) 823–835. E. Layre et al., Chem. Biol. 18 (12) (2011) 1537–1549. M. Zoeller et al., Plant Physiol. 160 (1) (2012) 365–378. Y. Okazaki et al., Metabolomics 9 (1) (2013) 121–131. M. Jove et al., Sci. Rep. 3 (2013). T.C.e.S. Consortium, Science 282 (5396) (1998) 2012–2018. H. Qadota et al., Gene 400 (1–2) (2007) 166–173. S.E. Hulme, G.M. Whitesides, Angew. Chem. Int. Ed. 50 (21) (2011) 4774– 4807. Y. Zhang et al., BMC Genomics 14 (1) (2013) 164. S. Hashmi et al., DNA Cell Biol. 27 (10) (2008) 545–551. S. Hashmi et al., Nutr. Metab. 10 (1) (2013) 31. J.L. Watts, J. Browse, Proc. Natl. Acad. Sci. 99 (9) (2002) 5854–5859. T.J. Brock, J. Browse, J.L. Watts, PLoS Genet. 2 (7) (2006) e108. C.L. Perez, M.R. Van Gilst, Cell Metab. 8 (3) (2008) 266–274. M. Kniazeva et al., PLoS Biol. 2 (9) (2004) e257. M. Nandakumar, M.-W. Tan, PLoS Genet. 4 (11) (2008) e1000273. J. Goudeau et al., PLoS Biol. 9 (3) (2011) e1000599. M. Kniazeva, T. Euler, M. Han, Genes Dev. 22 (15) (2008) 2102–2110. M. Kniazeva et al., Genes Dev. 26 (6) (2012) 554–566. J.L. Watts et al., Genetics 163 (2) (2003) 581–589. G.M. Lesa et al., J. Cell Sci. 116 (24) (2003) 4965–4975. R.J. Shmookler Reis et al., Aging (Albany NY) 3 (2) (2011) 125–147. M. Lucanic et al., Nature 473 (7346) (2011) 226–229. A. Folick et al., Science 347 (6217) (2015) 83–86. D. Schwudke et al., Anal. Chem. 79 (11) (2007) 4083–4093. L.H. Palavalli et al., Biochemistry 45 (19) (2006) 6056–6065. G. Lochnit, R. Geyer, Acta Biochim. Pol. 50 (4) (2003) 1239–1243.

[37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72]

[73] [74] [75] [76] [77] [78] [79] [80] [81] [82] [83] [84] [85] [86] [87] [88] [89] [90] [91] [92] [93] [94] [95] [96] [97] [98] [99] [100] [101] [102] [103] [104] [105] [106] [107] [108] [109] [110] [111]

L. Nilsson, E. Jonsson, S. Tuck, Traffic 12 (12) (2011) 1839–1849. V. Vásquez et al., Cell Rep. 6 (1) (2014) 70–80. E.V. Entchev et al., J. Biol. Chem. 283 (25) (2008) 17550–17560. D. Chitwood et al., Lipids 30 (6) (1995) 567–573. H. Zhu, H. Shen, A.K. Sewell, M. Kniazeva, M. Han, Elife. 2 (2013) e00429. V. Menuz et al., Science 324 (5925) (2009) 381–384. M.-B. Mosbech et al., PLoS One 8 (7) (2013) e70087. X. Deng et al., Science (New York, N.Y.) 322 (5898) (2008) 110–115. E.J. O’Rourke et al., Cell Metab. 10 (5) (2009) 430–435. Louis R. Lapierre et al., Curr. Biol. 21 (18) (2011) 1507–1514. Y.-H. Lin et al., Aging Cell 13 (4) (2014) 755–764. V.B. O’Riordan, A.M. Burnell, Biochemistry 92 (2) (1989) 233–238. W.G. Wadsworth, D.L. Riddle, Dev. Biol. 132 (1) (1989) 167–173. J. Kühnl et al., FEBS J. 272 (6) (2005) 1465–1477. R.J. Chandler et al., Mol. Genet. Metab. 89 (1–2) (2006) 64–73. T.V. Kurzchalia, S. Ward, Nat. Cell Biol. 5 (8) (2003) 684–688. D.L. Motola et al., Cell 124 (6) (2006) 1209–1223. P. Mahanti et al., Cell Metab. 19 (1) (2014) 73–83. H. Hsin, C. Kenyon, Nature 399 (6734) (1999) 362–366. T.M. Yamawaki et al., PLoS Biol. 8 (8) (2010) e1000468. J.R. Berman, C. Kenyon, Cell 124 (5) (2006) 1055–1068. M. Thondamal et al., Nat. Commun. 5 (2014). D.J. Chitwood, R. Lozano, W.R. Lusby, J. Nematol. 18 (1) (1986) 9–17. F. Broué et al., Aging Cell 6 (1) (2007) 87–94. S. Penkov et al., Angew. Chem. Int. Ed. 49 (49) (2010) 9430–9435. C. Mörck et al., Proc. Natl. Acad. Sci. 106 (43) (2009) 18285–18290. B.C. Persson et al., Biochimie 76 (12) (1994) 1152–1160. T. Jonassen, P.L. Larsen, C.F. Clarke, Proc. Natl. Acad. Sci. 98 (2) (2001) 421– 426. P. Ranji et al., PLoS One 9 (6) (2014) e100033. M. Rauthan, M. Pilon, Lipids Health Dis. 10 (1) (2011) 243. P.-Y. Jeong et al., Nature 433 (7025) (2005) 541–545. J. Srinivasan et al., Nature 454 (7208) (2008) 1115–1118. E.Z. Macosko et al., Nature 458 (7242) (2009) 1171–1175. J. Srinivasan et al., PLoS Biol. 10 (1) (2012) e1001237. Frank C. Schroeder, Chem. Biol. 22 (1) (2015) 7–16. X. Zhang et al., Acyl-CoA oxidase complexes control the chemical message produced by Caenorhabditis elegans, in: Proceedings of the National Academy of Sciences, 2015. K. Ashrafi et al., Nature 421 (6920) (2003) 268–272. H.Y. Mak et al., Nat. Genet. 38 (3) (2006) 363–368. F. Hu et al., Analyst 139 (10) (2014) 2312–2317. L. Wei et al., Nat. Meth. 11 (4) (2014) 410–412. H.J. Lee et al., Sci. Rep. 5 (2015). K. Yen et al., PLoS One 5 (9) (2010) e12810. G.J. Tserevelakis et al., PLoS One 9 (1) (2014) e84431. T. Hellerer et al., Proc. Natl. Acad. Sci. 104 (37) (2007) 14658–14663. T.T. Le et al., J. Lipid Res. 51 (3) (2010) 672–677. G. Patti et al., Metabolomics 10 (4) (2014) 737–743. F.M. Geier et al., Surf. Interface Anal. 45 (1) (2013) 234–236. J. Folch, M. Lees, G.H.S. Stanley, J. Biol. Chem. 226 (1) (1957) 497–509. E.G. Bligh, W.J. Dyer, Can. J. Biochem. Physiol. 37 (8) (1959) 911–917. V. Matyash et al., J. Lipid Res. 49 (5) (2008) 1137–1146. S. Chen, M. Hoene, J. Li, Y. Li, X. Zhao, H. Häring, E.D. Schleicher, C. Weigert, G. Xu, R. Lehmann, J. Chromatogr. A 1298 (2013) 9–16. P. Meister et al., Genome Biol. 12 (12) (2011) R123. P. Narayanaswamy et al., Anal. Chem. 86 (6) (2014) 3043–3047. C.K. Van Pelt, J.T. Brenna, Anal. Chem. 71 (10) (1999) 1981–1989. A.L. Michaud et al., Anal. Biochem. 307 (2) (2002) 348–360. J.G. Bollinger et al., J. Lipid Res. 54 (12) (2013) 3523–3530. V. Matyash et al., PLoS Biol. 2 (10) (2004) e280. D. Schwudke et al., Anal. Chem. 78 (2) (2006) 585–595. C. Papan et al., Anal. Chem. 86 (5) (2014) 2703–2710. M. Ishida et al., Rapid Commun. Mass Spectrom. 18 (20) (2004) 2486–2494. M. Witting et al., Anal. Bioanal. Chem. 407 (4) (2015) 1059–1073. C. Castro et al., Mol. BioSyst. 9 (7) (2013) 1632–1642. J.P. Chan, Z. Hu, D. Sieburth, Genes Dev. 26 (10) (2012) 1070–1085. L. Sumner et al., Metabolomics 3 (3) (2007) 211–221. V.A. Sarpe, S.S. Kulkarni, J. Org. Chem. 76 (16) (2011) 6866–6870. R. Csuk et al., Tetrahedron Lett. 54 (18) (2013) 2274–2276. K.K. Sharma et al., Mol. Endocrinol. 23 (5) (2009) 640–648. N. Sun et al., Proteomics (2014). p. n/a-n/a. A. Ly et al., Histochem. Cell Biol. (2014) 1–10. M. Sud et al., Nucleic Acids Res. 35 (suppl 1) (2007) D527–D532. Boyce Thompson Institute, C.U. C. elegans Small Molecule Identifier Database (SMID DB), 2011, Available from: . Y. Simón-Manso et al., Anal. Chem. 85 (24) (2013) 11725–11731. D.S. Wishart et al., Nucleic Acids Res. 41 (Database issue) (2013) D801–D807. D.S. Wishart et al., Nucleic Acids Res. (37 Database) (2009) D603–D610. M. Hansen, T. Flatt, H. Aguilaniu, Cell Metab. 17 (1) (2013) 10–19.

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The Caenorhabditis elegans lipidome: A primer for lipid analysis in Caenorhabditis elegans.

Lipids play important roles in biology, ranging from building blocks of membranes to signaling lipids. The nematode and model organism Caenorhabditis ...
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