(Glyco)sphingolipidology: an amazing challenge and opportunity for systems biology

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(Glyco)sphingolipidology: an amazing challenge and opportunity for systems biology Alfred H. Merrill Jr1, May Dongmei Wang1, Meeyoung Park1 and M. Cameron Sullards2 1

Schools of Biology, Chemistry and Biochemistry, the Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA 2 The Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia 30332, USA

Sphingolipids are found in essentially all eukaryotes and in some prokaryotes and viruses, where they influence cell structure, signaling and interactions with the extracellular environment. Because of the combinatorial nature of their biosynthesis, the sphingolipidome comprises untold thousands of species that encompass bioactive backbones and complex phospho- and glycolipids. Mass spectrometry is able to analyze a growing fraction of the sphingolipidome and is beginning to provide information about localization. Use of these structure specific, quantitative methods is producing insights, and surprises, regarding sphingolipid structure, metabolism, function and disease. Dealing with such large data sets poses special challenges for systems biology, but the intrinsic and elegant interrelationships among these compounds might provide a key to dealing with the complexity of the sphingolipidome. Sphingolipids in the age of systems biology Research in the biological sciences is shifting from primarily ‘reductionist’ to ‘systems’ approaches, in which one seeks to understand how all of the pertinent components interact functionally over time and under varying conditions, including disease [1,2]. The tools of systems biology are the ‘omics’ (genomics, proteomics and metabolomics, inter alia) that are responsible for quantifying every gene, protein and metabolite, respectively, in biological system(s) of interest as well as organizing the data to make it accessible for cross-platform computational analysis. Initiatives such as the LIPID MAPS Consortium (www. lipidmaps.org) have been developing analytical methods to identify and quantify all of the lipid subspecies of mammalian cells using mouse macrophages and RAW264.7 cells as prototypes. Nearly two thousand molecular subspecies have been surveyed thus far using primarily new methods developed by the Consortium (for examples, see references [3–5]), and the total lipidome (i.e. for all organisms) could be several orders of magnitude larger than this. The large size of the lipidome is in part because of its combinatorial nature (i.e. lipids are biosynthesized from subunits that can be Corresponding author: Merrill, A.H. Jr ([email protected]). www.sciencedirect.com

assembled in a multitude of combinations and with subtle modifications). Such large amounts of information necessitate a systematic nomenclature and structure database system [6,7]. While lipidomics is still in an early ‘discovery’ stage, its practitioners are making useful discoveries, such as new biomolecules [8], known metabolites in unexpected places [9] and new functions for preexisting compounds [10]. In this review we describe one subcategory of the lipidome, the sphingolipids, and discuss some of the daunting challenges, surprising findings and exciting opportunities that are surfacing as mass spectrometry (MS) is being used to characterize the sphingolipidome [4,10–14]. Structural and functional diversity of sphingolipids Sphingolipids are found in essentially all animals, plants and fungi, some prokaryotic organisms and viruses, as components of membranes, lipoproteins, skin and other important biological structures. As shown in Figure 1, they are defined as a category by the presence of novel aminecontaining lipid backbones (the so-called sphingoid bases: sphingosine, sphinganine and dozens of others) to which can be attached amide-linked fatty acids and (or) a headgroup at the primary hydroxyl, which range in complexity from a simple -H in ceramide to highly complex glycoconjugates (such as the tetra-sialosylglycosphingolipids found in placenta that have >20 carbohydrates) [15]. To contemplate the rationale for such structural diversity, Figure 1a shows a schematic diagram of current hypotheses about how sphingolipids are thought to function. They are located predominantly in the plasma membrane of mammalian cells, but there is a growing appreciation that sphingolipids also have intracellular functions [16], including in the nucleus [17]. The first function of sphingolipids is structural. The chemical properties of sphingomyelins and glycosphingolipids are well suited to formation of specialized microdomains that favor clustering for biologically useful purposes (for example, to form caveolae and membrane ‘rafts’) by organization of certain categories of membrane proteins, induction of membrane curvature and other specialized interactions [Figure 1a(i)] [18,19]. Complex glycosphingolipids, and sometimes phosphosphingolipids, serve as adhesion sites for proteins

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Figure 1. An overview of mammalian sphingolipid structure and function. Panel (a) shows a model plasma membrane with representative categories of sphingolipids [for the key to these symbols, refer to Panel (b)] and functions that have been attributed to complex species (sphingomyelins, gangliosides, and others), such as formation of membrane ‘rafts’ (i), binding to cell surface (ii) and extracellular (iii) proteins as well as intracellular signaling owing to formation of bioactive backbones [shown in the box, in the order: ceramide 1-phosphate, ceramide, sphingosine and sphingosine 1-phosphate, (S1P)] by turnover of (iv) complex sphingolipids and (v) de novo biosynthesis. At least one species (S1P) is also involved in extracellular signaling as represented by the green arrow (vi). The lower panels (b–d) show representative structures, nomenclature (including the root glycan families) and symbols that can be used for this family of compounds. These are consistent with recommendations by IUPAC [43], the LIPID MAPS Consortium (www.lipidmaps.org) and the Consortium for Functional Glycomics (http://www.functionalglycomics.org/fg/) for these structural components (the symbols for phosphate, P-choline, and sulfate have been assigned for the convenience of this article because there is currently no convention for these headgroups). Abbreviations: choline-P, choline phosphate; Fuc, fucose; Gal, galactose; GalNAc, N-acetylgalactosamine; Glc, glucose; GlcNAc, N-acetylglucosamine; NeuAc, N-acetylneuraminic acid; NeuGc, N-glycoloylneraminic acid.

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(and carbohydrates) from the extracellular matrix [20,21], neighboring cells [22], and bacteria and viruses [23], as shown in Figure 1a(ii) with ganglioside GM1 as an example [Figure 1a(ii),c]. Additionally, glycosphingolipids modulate the function of the proteins on the same cell [Figure 1a(iii)]; an often cited example is the inhibition of the epidermal growth factor (EGF) receptor tyrosine kinase by ganglioside GM3, which has been suggested to be due to a glycan– glycan interaction involving multivalent GlcNAc termini on the EGF receptor [24]. Glycosphingolipids also mediate cross-talk between growth factor receptors and integrins [25]. The functional unit in which glycosphingolipids play important roles in cell surface signaling, from stabilization of microdomains involved in carbohydrate-dependent cell adhesion to modulation of signal transduction, has been referred to as a ‘glycosynapse’ [26]. The backbone ceramides and sphingoid bases (and the metabolites of both) serve as mediators of intracellular and extracellular signaling, as is also shown in Figure 1a(iv). These bioactive species can be produced by turnover of complex sphingolipids (as shown for hydrolysis of sphingomyelin to ceramide [Figure 1a(v)] and by way of de novo biosynthesis [Figure 1a(vi) and Figure 2]. The utilization of sphingolipids for cell signaling allows regulation in multiple, potentially synergistic, steps. When a particular sphingolipid is removed from a membrane during its turnover to ceramide (or new sphingolipids are added to membranes by way of de novo biosynthesis), this will alter the properties of the membrane rafts and other structures [27,28] and enable changes in membrane curvature [29], transbilayer (flip-flop) movement of lipids [30] and other molecules [31]. The product(s) can also serve as second messenger(s) for intracellular protein targets and pathways, which in the case of ceramide [the initial turnover product shown in Figure 1a(v)] includes phosphoprotein phosphatases 1 and 2A, many members of the protein kinase C (PKC) family and Cathepsin D, just to name some of the known targets [32]; this illustrates the wideranging responses that can be triggered as well as the potentially profound consequences, because ceramide can induce programmed cell death [32]. An intriguing cell behavior that has been recently discovered to be induced by both ceramide [33,34] and de novo synthesized dihydroceramide [10] is autophagy, a process used by cells to turn over damaged organelles and to produce critical nutrients during starvation, and which has been found to be involved in a wide range of diseases, from cancer to neurodegenerative disease. Ceramide can subsequently undergo phosphorylation to ceramide 1-phosphate, a mediator that is associated with phagocytosis [35], stimulation of DNA synthesis [36], inhibition of apoptosis [37] and activation of phospholipase A2 and eicosanoid production [38]. To complicate matters even further, ceramide can be hydrolyzed to sphingosine, which produces a highly bioactive metabolite with its own intracellular targets (as recently reviewed) [10], including the first finding of a role for sphingosine as a ligand for a nuclear receptor, the steroidogenic factor (SF1), an orphan nuclear receptor that is essential for steroid hormone-biosynthesis and endocrine development [39]. Next, sphingosine undergoes phosphorylation to sphingosine www.sciencedirect.com

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1-phosphate, yet another signaling mediator for cell growth, survival, migration and other functions that are so complex that they are further arguments for ‘sphingolipidomics’ [40] [Figure 1a (iv,v)]. Additionally, these are not the only ‘lyso-’sphingolipids that have been found to be involved in cell regulation [41,42]. The sphingolipidome Panels (b)–(d) of Figure 1 introduce the structures, nomenclature and ways of graphically representing the sphingolipids that are found in mammalian cells, and the complexity of the full sphingolipidome is shown in illustrations of the subsequent pathway models (Figures 2–4). There are many different ways of naming and depicting these compounds depending on the molecular detail that one wishes to show. The recommendations of the International Union of Pure and Applied Chemists (IUPAC) [43] have been utilized mostly by groups such as LIPID MAPS in collaboration with scientists worldwide (including members of the Japanese Lipid Bank, http://www.lipidbank.jp, and the European Lipidomics Initiative, http://www. lipidomics.net/) that have been attempting to develop a system of nomenclature and depiction that is similar for different lipid classes [6]. A substantial number of sphingolipids are still referred to by historical names (for example, sphingomyelin instead of ceramide phosphocholine), or by the Svennerholm system that describes gangliosides by the number of sialic acid residues (GM for monosialo-, GD for disialo-, etc.). Yet another system that is widely used [43] is to name complex glycosphingolipids based on their root structures (Figure 1b). Using the ganglio- (Gg) root structure for ganglioside GM1, it would be abbreviated as II3Neu5AcGg4Cer. Modifications to the headgroup are added to the name, such as acetylation of sialic acid at position 9 (9-O-acetyl-) or formation of an ester between this hydroxyl and the carboxylic acid at position 1 of the adjacent sialic acid (e.g. GD1b-lactone, which is found in significant amounts in the nervous system) [18]. The complex headgroups of the sphingolipids are comprehended most easily by visual representation, either by the explicit ChemDrawß structure (shown in Figure 1c for ganglioside GM1a) or by the short-hand colored symbols (as shown in Figure 1a and b, and as a backdrop to the ChemDrawß image in Figure 1c) that have been widely adopted, including by the Consortium for Functional Glycomics (http://www.functionalglycomics. org/fg/) and by the Kyoto Encyclopedia of Genes and Genomes (KEGG), which has established a glycan resource tool (http://www.genome.jp/kegg/glycan/) [44]. Structural complexity is not limited to the headgroups, and Figure 1d shows the major structural variants of the sphingoid bases and ceramides of mammalian cells. For most tissues, sphingosine (abbreviated d18:1 for having two ‘di’-hydroxyl-groups, an 18-carbon chain length and one double bond) is the major sphingoid base backbone. Exceptions include: epithelial cells and skin, which often have high amounts of 4-hydroxysphinganine (hence, with three hydroxyl-groups, ‘tri’ is abbreviated t18:0); brain gangliosides, which have eicosasphingosine (d20:1) [45]; and, albeit in small amounts, plasma and neurons, in which sphingadiene (4-trans, 14-cis d18:2) has been found

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Figure 2. Mammalian sphingolipid biosynthesis pathway depictions. Panel (a) shows the steps of ceramide biosynthesis with the intermediates and enzyme names as usually depicted [with the link to the KEGG pathway, http://www.genome.jp/kegg/glycan/, represented by panel (b)]; boxes (a)(i) and (a)(ii) (pale blue backgrounds) show reactions that can produce additional bioactive metabolites. Ceramide is at the branchpoint [panel (c), pale green background] for formation of sphingomyelins, ceramide 1phosphates (Cer-P), glucosylceramides (GlcCer), galactosylceramide (GalCer), and 1-acylceramide, or can be turned over to sphingosine [(a)(ii)]. Also shown are the pathways for the sulfatides (c) and root family glycans and representative gangliosides [(d), pale red background] using short-hand symbols for the headgroups. The combinatorial nature of glycosphingolipid biosynthesis is shown in (e) (pale orange background; modified from [73]): SAT refers to sialyltransferase; GalNAcT and GalT to glycosyltransferases for UDP-GalNAc and UDP-Gal, respectively; the isomeric gangliosides GM1a and GM1b are highlighted in the box with broken lines. Note, the same shape and color scheme as in Figure 1b has been used in this figure.

[46]. The nature of the fatty acid that is attached to the sphingoid base also varies among different sphingolipid subtypes and across tissues; perhaps the most unusual fatty acids are found in skin ceramides (v-hydroxy-fatty acids with very-long-chain lengths, some of which are covalently attached to protein) [47]. When the fatty acyl www.sciencedirect.com

chain length is specified, this is often shown by the carbon number before the name, such as C16-Cer for N-palmitoylsphingosine; however, it is less ambiguous to use the shorthand nomenclature [6] that specifies both the sphingoid base backbone and fatty acid (e.g. d18:1/16:0 for Npalmitoylsphingosine). Considering these headgroup and

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Figure 3. The broader scope of mammalian sphingolipid biosynthesis. Panel (a) (pale blue background) depicts de novo sphingolipid biosynthesis and the scope of the sphingolipidome if one displays all of the individual species. The biosynthesis starts with the reaction catalyzed by serine palmitoyltransferase (SPT) and the formation of the different chain-length subspecies of N-acylsphinganines (d18:0/fatty acids) by the CerS (Lass) family of ceramide synthases (shown with their fatty acyl-CoA selectivities). This is followed by introduction of the double bond by dihydroceramide desaturases (DES1 and DES2) to form N-acylsphingosines (d18:1/fatty acid) (modified from [10]). Panel (b) (upper portion, gray background) illustrates for one backbone subcategory how dihydroceramide (d18:0/16:0) and ceramide (d18:1/16:0) can be partitioned into sphingomyelin (SM), ceramide phosphate (Cer-P), glucosylceramide (GlcCer), galactosylceramide (GalCer). The red broken arrows indicate that headgroups might be similarly added to each backbone subspecies. Also shown (pale red background) is that each N-acyl species can be turned over to the backbone sphingoid base, which might be phosphorylated (or recycled, not shown). The lower portion of (b) (pale orange background) shows the estimated number of downstream products that can be made in each root category of glycosphingolipids (note, the expanded versions of these compressed diagrams are available at www.sphingomap.org). The nomenclature is from Figure 1d.

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Figure 4. A backbone relational depiction of mammalian sphingolipid biosynthesis. This alternative depiction of de novo sphingolipid biosynthesis displays: (a) the conventionally written pathway including novel compounds that have surfaced, such as the N-methyl-sphingoid bases [10] using the sphingolipidomic methods described in reference [4]; (b) a relational pathway with each species represented by a node (including sphingoid base derivatives such as the 1-phosphate and N-methyl-derivatives); (c) expansion of one of the backbone subspecies (d18:1/20:0) to show additional metabolites; this scheme can be further expanded to include all of the headgroup species depicted in Figure 3); and (d) a galactic overview of the relationships among sphingoid base backbone families; these examples show the variation in sphingoid base chain length when palmitoyl- and stearoyl-CoA are used to produce 18- and 20-carbon homologs, respectively, each of which can undergo further modification to form d18:1 and d20:1 sphingosines, t18:0 and t20:0 hydroxysphinganines, and d18:2 and d20:2 sphingadienes. Other sphingoid base variants, such as odd-chain length, branched chain, and additional hydroxy- sphingoid bases can be added to this diagram in a similar manner (although for most mammalian sphingolipids, the sphingoid bases are predominantly 18-carbons in length). Each triangle in (d) represents all the downstream metabolites that can be found from that sphingoid base backbone:amide-linked fatty acid subspecies, for example, all of the compounds in the expansion in (c). www.sciencedirect.com

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backbone variations, it should be evident that there is the potential for a tremendous number of different molecular species. Sphingolipidomic analysis An analysis would be defined as truly ‘omic’ if it determines all of the molecular species, which for mammalian sphingolipids could number in the tens of thousands considering that there are over 400 headgroup subcategories in mammals alone (www.sphingomap.org), and many are likely to have at least several to a few dozen backbone variants if one counts both major and minor sphingoid bases and fatty acids. Although sphingolipids can be analyzed by a variety of methods {for an overview, Ref. [48] covers many aspects of sphingolipid analysis by traditional means such as thinlayer chromatography (TLC), immunochemistry, etc.}, the most powerful approach today is tandem MS, which uses various ionization methods [mainly electrospray ionization, electrospray ionization (ESI), and matrix-assisted laser-desorption ionization, or MALDI] with the combination of tandem mass analyzers that is best matched to the project needs, such as triple quadrupole (QqQ) or tandem quadrupole-linear ion trap (QTrap) for tandem mass spectrometry (MS/MS) and MS3 [4], respectively, or for higher mass accuracy, quadrupole-time-of-flight (QTof) [49] or Fourier transform (FT) MS [50,51]. Current methods are able to analyze only a portion of the sphingolipidome quantitatively; a major limitation is the lack of internal standards for the more complex sphingolipids. Nonetheless, the current ‘sphingolipidomic’ methods encompass useful subsets such as: all of the biosynthetic intermediates to ceramide as well as its turnover to sphingosine versus incorporation into phosphosphingolipids (sphingomyelin, ceramide phosphoethanolamine or ceramide phosphate) or glycosphingolipids (glucosylceramide and galactosylceramide) [4]; all of the backbone subspecies that are involved in cell signaling [4,52]; sulfatides (in Alzheimer’s disease) [53]; and other lipid profiles such as the sphingolipids that are enriched in detergent-resistant membranes [54], viral membranes [55], lipoproteins [56], tissues such as hippocampus [49], and sphingolipid storage diseases such as Fabry’s [57,58]. The success of MS analysis fundamentally depends on whether or not the compounds of interest produce ions that are useful as unique and sensitive identifiers for the individual species. In this regard, sphingolipids have proven to be particularly amenable to mass spectrometric analyses because they are relatively easily ionized (which allows analysis of relatively small numbers of cells), and many fragment to products that are characteristic for the headgroup and backbone subclasses. For examples, both long-chain bases and complex sphingolipids readily ionize by way of ESI in the positive ion mode to form mainly positive ions of the original molecule plus a proton (M + H)+ ions, and sphingoid base-1-phosphates, sulfatides, sphingomyelins and gangliosides form strong ions of the type (M H) , (M 15) or (M nH)n (i.e. the original molecule minus a proton, a methyl- group or multiple hydrogens, respectively) by way of negative ion ESI, depending on the composition of the solvent (reviewed in Ref. [4]). Furthermore, the fragmentation www.sciencedirect.com

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profiles for both sphingoid bases and many complex sphingolipids provide information about the headgroups and types of sphingoid bases and fatty acids in the backbones, providing that one has the capacity for MS/MS and tandem MS (MSn) analysis. An analytical complication that must, nonetheless, be dealt with is the common occurrence of isomeric or isobaric species; consider, for example, the backbone isobars such as N-stearoyl-sphingosine (d18:1/18:0) versus N-palmitoyleicosasphingosine (d20:1/16:0), the root series compounds in Figure 1b or gangliosides GM1a and GM1b (Figure 2d). These can be distinguishable by their fragmentation patterns in MSn, but it is often desirable for them to be resolved chromatographically for unambiguous quantitation in complex mixtures [4]. Fortunately, various types of chromatography (liquid and TLC) and MS have been applied to sphingolipids for decades [48], hence, the combination of new and old methods, such as MS with TLC [50,59], should accelerate the solution of these difficult analytical challenges. One of the promising enhancements of these approaches has been the development of automated microfluidic ‘chip’-based devices for nanoelectrospray tandem MS which, when coupled to a high resolution, accurate mass analyzer, can provide molecular formula determination in MS mode and sophisticated structural information at high sensitivity in MS/MS [49]. For the analyses to be quantitative, investigators must have access to a sufficiently complete series of internal standards to account for differences in extraction efficiency, ionization and fragmentation. This is done by adding validated internal standards, and several individual internal standards and internal standard ‘cocktails’ have been identified by the Lipid Maps Consortium and are listed on their website (www.lipidmaps.org) as well as commercially available (from Avanti Polar Lipids, Alabaster, AL, www.avantilipids.com, for sphingolipids). One of the next challenges is to obtain information about metabolic flux, which is usually done using stable isotope precursors combined with MS [4,60] and isotopomer analysis [61]. And as these types of information become available, researchers can begin to develop computational and visualization models for sphingolipid metabolism by mammalian cells [62], as has begun with yeast [63]. An ‘omic’ view of sphingolipid metabolism The purpose of developing these ‘omic’ tools is to be able to know what specific compounds are present during a biological process of interest, and in many cases to know where they come from and how they are removed. The pathway for de novo sphingolipid biosynthetic pathway as typically shown (Figure 2a and the equivalent pathway on the KEGG web link given in Figure 2b) begins with condensation of serine and palmitoyl-CoA by serine palmitoyltransferase to form 3-ketosphinganine, which is reduced to sphinganine, N-acylated to dihydroceramide and desaturated to ceramide, which is incorporated mainly into sphingomyelin, glucosylceramide, galactosylceramide and ceramide 1-phosphate (Figure 2c). As these ‘simple’ steps have been reexamined using ‘omic’ methods, some of the findings have been consistent with this pathway whereas others have been quite surprising [10].

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It has long been perceived that the amounts of the early intermediates of sphingolipid biosynthesis are kept low to minimize cytotoxicity [64], and this has been confirmed by quantitative analyses using MS [4,11,65]; these analyses typically find that 3-ketosphinganine is undetectable (<1 pmol/106 cells) and sphinganine amounts are generally very low (10 pmol/106 cells), compared with ceramides and sphingomyelins, which are on the order of 100–300 pmol/106 cells and 1000–3000 pmol/106 cells, respectively [4,11,65]. The importance of this control surfaced when the discovery was made that a family of mycotoxins (fumonisins) cause a wide spectrum of diseases as inhibitors of ceramide synthase [66]. By blocking this enzyme [see red highlight in Figure 2a(i)], fumonisins cause large elevations in sphinganine, which is highly cytotoxic. Provocatively, a neighboring metabolite of sphinganine is sphinganine 1-phosphate, which is mitogenic and anti-apoptotic [40], and mass spectrometric analysis has revealed that fumonisins elevate sphinganine 1-phosphate in some cells [11], which is likely to account for the ability of fumonisins to be both toxic (by way of sphinganine) and carcinogenic (by way of sphinganine 1-phosphate). Until relatively recently, little was known about ceramide synthase(s); however, almost immediately after the cloning of the yeast genes, the first mammalian homolog (Uog1, now named Lass1 or CerS1) [67] was found by liquid chromatography MS/MS (LC MS/MS) to make, essentially, only C18-(dihydro)ceramide. Soon after LASS1 was identified, head and neck tumors were discovered to have lower proportions of C18-ceramides than neighboring normal tissue, and transfection of the CerS1 (Lass1) gene into related tumor cells in culture suppressed cell growth [68]. Subsequent studies have uncovered that CerS1 (LASS1) and C18-ceramide are important in chemotherapy-induced cell death in human head and neck squamous cell carcinomas [69]. These findings exemplify how particular chain-length ceramides are metabolically and functionally distinct. There are at least six genes for the Cer synthase family [which are sometimes referred to as the ‘(dihydro)ceramide synthases’ because they also make dihydroceramides], Lass1 to Lass6 or CerS1 to CerS6, in mammalian cells. Each isoform appears to utilize a somewhat different profile of fatty acyl-CoAs as summarized in Figure 3a [70]; therefore, it is now antiquated to refer to generic ‘ceramides’ rather than to describe specific subspecies for some biological functions. The next step of de novo sphingolipid biosynthesis, conversion of dihyroceramides to ceramides (Figure 2a), is thought also to be critical because the 4,5-trans double bond has been reported to be required by many of the signaling targets of ceramides, including the induction of growth arrest and apoptosis [71]. Thus, it is intriguing to find that a substantial fraction of the ‘ceramides’, sometimes even the majority [65], are dihydroceramides in some cancer cell lines [65,72]. In perhaps the greatest surprise to date, a promising anti-cancer drug, fenretinide (4-hydroxyphenylretinamide), that has been thought to elevate ceramide as part of its mechanism of action, instead actually inhibits dihydroceramide desaturase and elevates dihydroceramides, which induce lethal autophagy [10]. www.sciencedirect.com

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The application of MS has uncovered other novel – and potentially (patho)physiologically relevant – species, such as N-acyl-3-ketosphinganines and N-methyl-sphingoid bases [10]; therefore, we have entered a ‘sphingolipidomic’ era where it will be difficult to draw definitive conclusions about the role(s) of the lipid backbones in cell regulation without using these types of comprehensive methodologies. Combinatorial sphingolipid metabolism Panels (c) and (d) of Figure 2 (as well as Figures 3 and 4) illustrate another fundamental concept of complex sphingolipid biosynthesis, that it is comprised of a large number of branchpoints where intermediates partition into several possible products; hence, the amounts and types of each is determined by the activities of key enzymes, the subcellular localization of the enzymes and substrates (which is a function of the rate of transport to and from a given subcellular locale), as well as the relative rates of biosynthesis versus turnover. The ‘combinatorial’ nature of glycosphingolipid biosynthesis, as it has been termed [73], helps explain the large numbers of compounds that can be made (i.e. many more than just the number of genes dedicated to this pathway) and the consequences of manipulation of the activities of particular enzymes in the pathway by biochemical means or genetic engineering [73,74]. Note, for example, that two isomers of ganglioside GM1 (i.e. GM1a and GM1b in Figure 2e) differ only in the location of the a3-sialic acid, which is determined by whether lactosylceramide is first sialylated to ganglioside GM3 [by sialyltransferase I (SAT I)] to produce GM1a or first converted to GA2 (asialoGM2) by GalNAcT for GM1b. As predicted, SAT Ideficient mice are not able to form GM3 and, consequently, none of the subsequent gangliosides in the GM3, GM2, GM1a series; however, they form GM1b and others in this series (Figure 2e) [75]. The consequences of loss of a particular branchpoint can, nonetheless, still produce new surprises. For example, when galactosylceramide biosynthesis was eliminated by knockout of UDP-galactose:Cer galactosyltransferase (abbreviated CGalT or CGT), some of the neurological consequences might be ameliorated by formation of hydroxy-GlcCer [76]. In addition, one must always keep in mind that blockage of one step causes the buildup of the substrate and/or diversion of intermediates to alternative pathways, and these can be highly bioactive (e.g. ceramide, sphingoid bases or 1-phosphates inter alia) [Figure 2a(i,ii)]. What is the potential magnitude of the sphingolipidome considering that such a large family of biomolecules can be generated by relatively few enzymes? This is not currently known but is being addressed by computational prediction of glycan structures from gene expression data based on glycosyltransferase reactions [77]. However, it must be borne in mind that the sphingolipidome comprises variations in both the backbone (Figure 3a) and headgroup (Figure 3b), hence, the magnitude could be on the order of 104 based on just the shown subspecies. It is evident that the layout of the pathway as modeled in Figure 3 does not allow more than one or two backbone subcategories to be shown at a time, and interrelationships will be difficult to discern if the diagrams become more

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complex. In place of this format of layout, we recommend the backbone relational scheme shown in Figure 4 because it defines a spatial order that conveys structural information not only about the backbone composition (for example, all of the compounds in one spoke of the wheel share the same backbone), but also, about the headgroup, because a given headgroup will appear at regular intervals around each wheel. This layout can be used to display changes in metabolites by a variety of highlighting schemes, with perhaps the simplest being to assign ‘hot scale’ colors (red for increases, green or blue for decreases) to the compounds that change or differ between two groups. This type of tool would be useful not only for the identification of differences but also in the interpretation of changes that might be tagged by a bioinformatics tool, such as principle component analysis, because investigators will ultimately need to think about the metabolic and functional implications of such findings. Location, location, location To complicate matters further, when one examines the sphingolipids in tissues, different regions often vary in the types that are present, as exemplified by the central nervous system [78], and even when analyzing single cells, the subcellular localization of sphingolipids and their metabolic enzymes, transport proteins and targets will influence their fate and function [16,73,79]. This is encountered from the earliest steps of sphingolipid biosynthesis, in which: ceramide is made in the endoplasmic reticulum (ER) and converted to sphingomyelin in both the Golgi and at the plasma membrane [80] with an apparent involvement of the ceramide transport protein, CERT [81]; galactosylceramide is synthesized in the lumen of the ER [82]; and glucosylceramide is synthesized on the cytosolic side of the Golgi apparatus (and possibly the smooth ER) [16,79]. Higher order glycosphingolipids are biosynthesized inside the Golgi; hence, they must be transported from the cytoplasmic site of synthesis to the lumen for the subsequent steps [16,73,79]. Interestingly, the multiple drug resistance pump (MDR1) is one of the transporters for glucosylceramide [83] but appears to be involved only in the biosynthesis of neutral glycosphingolipids and not gangliosides, even though they theoretically share the same precursor. This not only leaves open the question of how the biosynthetic precursors for gangliosides enter the Golgi, but also, whether this is one of the reasons why glycosphingolipids often have different lipid backbones even though they share common biosynthetic intermediates. Some backbone selectivity appears to be exercised by glycosyltransferases [84], but it might arise also from differences in transport and reutilization of the products of salvage pathways and cell signaling [85]. Thus, the next level of complexity for sphingolipidomic analysis is localization of the compounds of interest with specific cells in a tissue and subcellular compartments. Molecular imaging using mass spectrometry Recent developments in MS are beginning to allow analysis of sphingolipids in situ using samples such as thin slices of tissue, cultured cells and model membranes. One of the methods is a variation of MALDI in which tissue www.sciencedirect.com

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slices are placed on a MALDI plate, imbedded as uniformly and non-disruptively as possible with matrix material (which serves to absorb laser light, volatilize and ionize nearby compounds of interest in the sample), then the laser beam is moved incrementally across the sample generating discrete mass spectra over the selected mass to charge (m/z) range using ToF MS to take advantage of its ability to couple with a pulsed ion source for high sensitivity and rapid mass analysis [86–88]. Specific m/z of interest can then be assigned different colors and plotted in x,y-space to yield a molecular image of the biological sample, which is often cross-referenced with histologic markers that can be visualized using standard methods using a neighboring tissue slice. In another technique, secondary ion MS (SIMS), a beam of primary ions is tightly focused to impinge on the surface of the biological material to ionize compounds of interest [87,89,90]. This technique provides greater spatial resolution for lower mass ions than MALDI, whereas MALDI is more amenable to higher mass species (but has a lower spatial resolution owing to the size of the laser spot). An additional technique, desorption electrospray ionization (DESI) uses charged droplets of solvent generated from an electrospray to generate the secondary ions [91]. The highest resolution technique, nanoSIMS (70–100 nm), uses a tightly focused beam of cesium ions (Cs+) to scan the sample and produces primarily mono- and diatomic secondary ions; therefore, for identification of the compound(s) of interest, it is necessary to prelabel them with a stable isotope such as 13C and 15N [92]. Applied to brain tissue, MALDI ToF has detected sphingomyelins, monohexosylceramides, sulfatides and gangliosides [86,88], as well as correlated certain subcategories with different brain regions; for example, that the cerebellar cortex contains small amounts of sphingomyelin but larger amounts of sulfatides and gangliosides GM1, GD1, and GT1, whereas the cerebellar peduncle contains sulfatides and primarily GM1 with smaller quantities of GD1 [86]. SIMS ToF of brain slices [90] revealed that chain length variants of galactosylceramide are differentially localized in white matter, with C18-subspecies being associated with cholesterol-rich regions, whereas C24-subspecies are found primarily in areas that are also enriched in Na+ and K+. Although imaging MS has limitations with respect to its ability to resolve isomeric and isobaric compounds and to provide quantitative information, the ability to know the cellular, and eventually subcellular, location of the analytes of interest will be a major complement to the ability to analyze the molecular subspecies profile and amounts using the other sphingolipidomic MS methods. Perspectives Whether research is reductionist or systems oriented, it is important to know the types and amounts of biomolecules that are present. Recent developments in MS and the continuing rapid evolution of new technologies, provide optimism that this information will become available for sphingolipids in the foreseeable future. What will be learned from the sphingolipidome? First, as discussed in this review, mainly the discovery of new metabolites and unexpected functions for known metabolites will be

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made. Thereafter, when the sphingolipidome can be related to the overall lipidome, there will be a more profound appreciation of how lipids perform ‘macromolecular’ functions as dynamic aggregates that are analogous to nucleic acids, proteins and complex carbohydrates. This analogy implies that abnormalities in lipid composition impact cell behavior as profoundly as defective genes or proteins, although this has often been difficult to discern because lipid compositions often adjust to suppress or ameliorate perturbations. One anticipates that lipidomics will allow this ‘big picture’ to be seen, and not only as a snap-shot, but also spatially and temporally. Indeed, scientists will ultimately achieve spatial–temporal reasoning, which means in the words of the collective authority of our era (http://en.wikipedia.org/wiki/Spatial-temporal_reasoning) ‘the ability to visualize spatial patterns and mentally manipulate them over a time-ordered sequence of spatial transformations. This ability, often referred to as ‘thinking in pictures’, is important for generating and conceptualizing solutions to multi-step problems that arise in areas such as architecture, engineering, science, mathematics, art, games (e.g. chess), and everyday life’, to which we would add ‘. . .and lipidomics.’ Acknowledgements The majority of the new findings described in this review were uncovered using resources provided by the Lipid MAPS Consortium grant (GM069338). The authors thank colleagues at Georgia Tech (Elaine Wang, Samuel Kelly, Jeremy Allegood, Chris Haynes and others), the LIPID MAPS Consortium (especially Walt Shaw for internal standard development, and Eoin Fahy and Shankar Subramaniam), the Complex Carbohydrate Research Center at the University of Georgia (Michael Pierce, Kelley Moremen and Will York, who contributed substantially to some of the concepts about ‘glycomics’ as part of the NIH grant PA-02– 132 for the Integrated Technology Resource for Medical Glycomics), and those at other institutions who have helped in the evolution of these ideas by their findings and discussions. This review is dedicated to Sen-itiroh Hakomori on the occasion of his recent birthday celebration.

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