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Published in final edited form as: ACS Chem Neurosci. 2016 Jun 20;7(8):1148–1156. doi: 10.1021/acschemneuro.6b00120

Ethanol Induced Brain Lipid Changes in Mice Assessed by Mass Spectrometry

Aurelie Roux †, Shelley N Jackson †, Ludovic Muller †,‡, Damon Barbacci ∥, Joseph O’Rourke §, Panayotis K Thanos §, Nora D Volkow †, Carey Balaban ⊥, J Albert Schultz ∥, Amina S Woods †,*
PMCID: PMC7577215  NIHMSID: NIHMS1622995  PMID: 27269520

Abstract

Alcohol abuse is a chronic disease characterized by the consumption of alcohol at a level that interferes with physical and mental health and causes serious and persistent changes in the brain. Lipid metabolism is of particular interest due to its high concentration in the brain. Lipids are the main component of cell membranes, are involved in cell signaling, signal transduction, and energy storage. In this study, we analyzed lipid composition of chronically ethanol exposed mouse brains. Juvenile (JUV) and adult (ADU) mice were placed on a daily limited-access ethanol intake model for 52 days. After euthanasia, brains were harvested, and total lipids were extracted from brain homogenates. Samples were analyzed using high resolution mass spectrometry and processed by multivariate and univariate statistical analysis. Significant lipid changes were observed in different classes including sphingolipids, fatty acids, lysophosphatidylcholines, and other glycerophospholipids.

Keywords: lipids, alcohol, electrospray ionization, solid-phase extraction, mass spectrometry

Graphical Abstract

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Alcohol abuse and alcoholism are characterized as multifactorial disorders responsible for various neurocognitive deficits or dysfunctions involving impairments in different brain regions or neural pathways. Drinking has dramatic effects on heath. It impairs the ability to work and fulfill responsibilities and is dangerous in many situations, including the operation of a motor vehicle or any type of machinery. As reported by the ISCD (Independent Scientific Committee on Drugs) in 2010, when harm to self and others is summed, alcohol was the most harmful of all drugs considered, scoring 72%.1 A US study from 2007 estimated that about 30% of Americans report having an alcohol disorder at some time in their lives.2 Moreover underage drinking in the USA is common; 26.6% of Americans under the legal age for alcohol consumption are drinking, according a recent report issued by the Substance Abuse and Mental Health Services Administration (SAMHSA).3 Alcohol passes through the blood–brain barrier, reaching neurons directly, and considering its widespread availability and consumption, it is considered as one of the most common neurotoxins. Even at low doses, alcohol can slow reflexes and reaction time, impair motor coordination and memory, and cause impulsive or aggressive behavior.4–7 Over time, drinking can cause serious and persistent changes in the brain, including significant disruption of the delicate balance between inhibitory and excitatory neurotransmitters.8,9 Ethanol can indeed modulate neurotransmitter molecule release in certain areas of the brain, especially dopamine and GABA but also glutamate and other endogenous neuroactive molecules like endorphins.10–14 Although the numerous effects of ethanol on the brain are well documented, the molecular mechanisms underlying those effects are still not completely understood.

Lipids are the most common biomolecules found in the brain after water. They make up half of the brain’s dry weight. They are the major building blocks of cell membrane, play a key role in cell signaling and signal transduction, and are an important reservoir of energy. There are many studies reporting the effect of alcohol-induced oxidative stress on organs15–18 and related induced molecular changes (including lipids) on cells such as hepatocytes and erythocytes.19–23 Indeed alcohol breakdown in the liver results in the formation of molecules whose further metabolism in the cell leads to ROS production, generating oxidative stress that disturbs lipid membrane structure (lipid peroxidation that modifies membrane fluidity and lipid rafts) and causes various other cellular injuries, such as DNA damage and protein modification.24,25

Most of the earlier studies dealing with the effect of ethanol consumption on brain lipids focus on membrane properties.26–29 These studies showed that ethanol increases the fluidity of synaptic membranes (but not myelin membranes). However, the fluidity effect is usually only seen at ethanol concentrations above the pharmacological range.30 Ethanol membrane toxicity can be attributed to the interaction of ethanol at the aqueous interface, its insertion into the lipid bilayer resulting in a perturbed membrane structure and function.31 However, the alterations in membrane fluidity cannot be explained only by the physicochemical properties of ethanol, and it has been demonstrated that ethanol also alters lipid metabolism.32,33 Lipids are the major components of cell membrane and therefore play a role in the membrane’s physical property changes. The increase of synaptic membrane fluidity has been correlated with changes in the phospholipid acyl composition but also changes in cholesterol concentrations.34,35 Cholesterol plays an important role in membrane response to alcohol consumption,27,36 but results from several studies are not consistent, some of them are reporting an increase in cholesterol,37,38 and others a decrease29 or no change.39 As for the fatty acyl composition of phospholipids, most of the studies reported a relative decrease of polyunsaturated fatty acids in phospholipids,29,34,35,39–41 but some studies did not report any changes.37 Variations in some classes of phospholipids were also reported,42,43 but again the results of these studies are not always consistent. These inconsistencies may be due to the variations of animal models, experimental design (especially the amount of EtOH given), sample preparation, or the diversity and lack of accuracy of the analytical methods used. Indeed, the majority of this work was conducted over 2 decades ago, before the advent of modern analytical techniques like biological mass spectrometry.

Most of these studies were conducted on adult animal models of alcohol consumption. Effects of ethanol on the developing fetal brain have also been extensively studied.36,44 Indeed alcohol consumption during pregnancy can have a dramatic effect on fetal brain development. Alcohol exposure during adolescence can also have long-lasting effects and interfere with normal brain functioning during adulthood.45–47 Even though the effect of ethanol on the juvenile brain has also been extensively studied,48,49 to our knowledge no assessment of alcohol effect on brain lipids in a juvenile model of alcoholism are available. In this study, we extracted and fractionated lipids from whole brain of both adult and juvenile chronically ethanol exposed mice. Lipids were then analyzed by high resolution mass spectrometry. The high resolution allowed us to reach a mass resolution of 100 000 and a mass accuracy under 5 ppm. Those parameters were very important for an accurate identification of lipids in each fraction. MS/MS analyses were also conducted to confirm the identification of the annotated lipids. We then performed different statistical analysis to accurately determine which classes of lipids or individual lipids were impacted by alcohol consumption in both adults and juvenile mice.

RESULTS AND DISCUSSION

The MS peak list from whole brain extract contains signals corresponding to 380 lipids from 16 lipid classes (Table S1). This lipid list was processed by multivariate analysis to highlight lipid class differences between control and alcohol consumption groups. Figure 1A shows the distribution of the samples, also known as a scores plot, on the first two components of the PLSDA (partial least squares discriminant analysis). The first component, LV1, represents 10.31% of the variation snf the second one, LV2, 11.48%. The sample distribution clearly shows that the group of alcohol adult rats (ADU EtOH) is very different from the three other groups. The ADU EtOH rats are separated completely from control adult rats (ADU H2O) and both juvenile groups (JUV EtOH and JUV H2O); this separation reflects differences in LV1 scores. The JUV H2O group is distinct from the ADU H2O group, with the JUV EtOH rats showing overlap with both control groups. The separation between the ADU H2O and JUV H2O is provided by component LV2 scores.

Figure 1.

Figure 1.

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PLSDA multivariate analysis of the lipids extracted from the mice whole brains: (A) samples/scores plot. (B) variables/loadings plot. (Cer, ceramides; FA, fatty acids; FACO, carbonylated fatty acids; FACOOH, carboxylated fatty acids, FAOH, hydroxylated fatty acids; GalCer, galactoceramides; LYSOPA, lysophosphatidic acids; LYSOPC, lysophosphatidylcholines; LYSOPG, lysophosphatidylglycerols; LYSOPI, lysophosphatidylinositols; LYSOPS, lysophosphatidylserines; PA/PM, phosphatidic acids/phosphatidylmethanol; PC, phosphatidylcholines; PE, phosphatidylethanolamines; PG, phosphatidylglycerols; PI, phosphatidylinositols; PS, phosphatidylserines; SM, sphingomyelins; ST, sulfatides) Results from Bonferroni-corrected t tests for peak differences between the ADU H2O and ADU EtOH are displayed in the PLSDA plot (*p < 0.05, **p < 0.01, ***p < 0.001).

The diagonal constructed with the two components, LV1 and LV2, gives good insight to the samples’ clustering (Figure 1A). The axes show separation according to alcohol consumption. The ADU EtOH group is on the far left of the diagonal while the ADU H2O group is on the far right. Juvenile groups are closer to the center, suggesting a less marked variation than in adults, and their position is also opposite: The JUV H2O group is on the left of the diagonal while the JUV EtOH group is on the right. The sample distribution on LV1/LV2 axes gives two important clues about the effect of alcohol in both age groups. The first one is that alcohol consumption has a greater impact on adult compared with juvenile rats (JUV groups overlap but ADU groups are very far from each other). The second effect is that alcohol consumption has a reverse effect in both age classes since the ADU and JUV EtOH groups have an opposite position regarding the diagonal axe (the same for H2O groups suggesting also basal differences in lipid composition in both control age groups).

The loadings plot in Figure 1B shows the relative contributions of the different classes of lipids to the latent variable (LV1 and LV2) scores that are plotted for the groups in Figure 1A. It shows the lipid classes responsible for the discrimination observed between the sample groups. The farther the variables are from the center of the plot, the more heavily they are weighted in the model discriminant function. Thus, variables on the top left of the plot contribute to the decreased LV1 score and increased LV2 score in ADU EtOH relative to the other groups. Two-way ANOVA and Bonferroni post-tests on the individual lipids (significant effects are listed in Table S1) showed that all ceramides (CER, red triangles), some fatty acids (FA, green circles), and some lysophosphatidylcholines (LysoPC, light green diamonds) were elevated significantly in the ADU EtOH group relative to the ADU H2O group. A few phosphatidylcholine (PC, yellow triangles) and phosphatidylethanolamine (PE, light blue triangles) species also increased significantly in the ADU EtOH group relative to ADU H2O. Lipids in the lower right box on the plot would contribute to the elevated LV1 score and lower LV2 score in the ADU H2O group relative to the ADU EtOH group. The ADU EtOH group showed significant decreases (relative to the ADU H2O group) for several phosphatidylmethanol (PM, purple triangles) and several sphingomyelins (SM, orange triangles) and a few PE.

Sphingolipids.

Sphingolipids constitute a class of lipids defined by a sphingoid base backbone. In this study, we detected 87 sphingolipids including 4 different classes: 16 ceramides (Cer), 19 sphingomyelins (SM), 33 galacto- or lactoceramides (GalCer/LacCer), and 19 sulfatides (ST). Levels of the identified ceramides were significantly higher in JUV H2O than ADU H2O (Table S1). Ceramide levels increased significantly in response to ethanol treatment in adult animals (ADU EtOH group relative to the ADU H2O group) but either decreased significantly or were unchanged after ethanol consumption in the juvenile animals (Figure 2). More comprehensive results for ceramide levels in juvenile and adult animals were reported in a previous paper.50 Among sphingomyelin (SM) species, only three species (SM C18:1/d18:1 or C18:0/d18:2) showed a significant difference between the ADU H2O and JUV H2O groups, but EtOH consumption decreased several SM species significantly in adults (Figure 2) while either slightly increasing or not affecting levels in juvenile animals. Cerebrosides (GalCer/LacCer and ST) showed no significant effects related to alcohol consumption (Figure 2).

Figure 2.

Figure 2.

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Comparison of the concentration of four brain sphingolipids (Cer, red; SM, green; GalCer, orange; ST, blue) in chronically alcohol exposed JUV and ADU mice (*p < 0.05, **p < 0.01, ***p < 0.001).

Fatty Acyls.

Fatty acyls constitute a class of lipids defined by a long carbon chain linked to a chemical group (such as an acid, alcohol, or ether). We detected 39 fatty acids and conjugates including 4 different classes: 25 free fatty acids (FA), 4 carbonated fatty acids (FACO), 3 carboxylated fatty acids (FACOOH), and 7 hydroxylated fatty acids (FAOH). As suggested by Figure 1B, some free fatty acids are impacted by alcohol consumption. Six of them (6/25) exhibit significant changes between the ADU EtOH and controls: intensities in ADU EtOH are significantly higher than those in ADU H2O, but no significant changes were observed between JUV groups (Figure 3). All but one of the modified fatty acids showed no differences as a function of either age or ethanol consumption. Figure 3 illustrates two examples of modified fatty acids, FA C22:0(COOH) and FA 18:2(OH).

Figure 3.

Figure 3.

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Comparison of the concentration of four fatty acyls (FA, green; FACOOH, blue; FAOH, orange) in ADU and JUV chronically alcohol exposed mice (*p < 0.05, **p < 0.01, ***p < 0.001).

Glycerophospholipids.

Glycerophospholipids or phosphoglycerides are glycerol-based phospholipids. They contain a glycerol backbone, to which one or two fatty acids and a phosphoric acid (that can be modified) are attached as esters. We detected 254 glycerophospholipids from 11 different classes: 3 lysophosphatidic acids (LysoPA), 5 lysophosphatidylcholines (LysoPC), 2 lysophosphatidylglycerols (LysoPG), 4 lysophosphatidylinositols (LysoPI), 6 lysophosphatidylserines (LysoPS), 10 phosphatidic acids (PA), 7 phosphatidylmethanol (PM), 90 phosphatidylcholines (PC), 64 phosphatidylethanolamines (PE), 13 phosphatidylglycerols (PG), 14 phosphatidylinositols (PI), and 36 phosphatidylserines (PS). Only LysoPC, PE, and PM showed significant changes with alcohol consumption.

The LysoPC position in Figure 1B suggests that they behave in a manner similar to the ceramides; four of the five species exhibit significant increases in the ADU EtOH relative to the ADU H2O group, but no significant effects of EtOH consumption appeared in the juvenile animals (Figure 4). The effects of ethanol consumption varied among the few PE species (5/64) that showed any significant response (Table S1). Initially, we thought some phosphatidic acids showed significant changes with alcohol consumption; 7 of them exhibited lower intensities in ADU EtOH compared with ADU H2O, but no significant changes were found between JUV groups (Figure 4). Interestingly all significant PA had odd numbers of carbons, which is not common in mammalian tissue (Table S1). MS/MS experiments were performed on these species, and it was determined that they were PM not PA as discussed below.

Figure 4.

Figure 4.

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Comparison of the concentrations of four glycerophospholipids (LysoPC, light green; PM, purple) in chronically alcohol exposed JUV and ADU mice (*p < 0.05, **p < 0.01, ***p < 0.001).

The CID spectrum for m/z 661.4814 that was initially assigned as PA 33:0 based on MS data is shown in Figure 5. The fragmentation pattern clearly shows the loss of fatty acid 16:0 and no other fatty acid. This is not consistent with a PA 33:0 but a PA 32:0 (16:0/16:0) with an extra CH2 not located on the side chains (according to the fragmentation pattern). This suggests that the headgroup contains an extra CH2 and thus the PA is in fact a PM. Because of the low mass cut off, the headgroup ion was not detected; however compared with a standard of PM (16:0/16:0) (Figure 5), the fragmentation pattern is identical. Another example is the fragmentation pattern of m/z 709.4814 (initially assigned as PA 37:4), shown in Figure 6. It clearly shows the loss and the ion for the side chains 20:4 and the ion for the side chains 16:0. Compared with a standard of PA (17:0/20:4), the fragmentation pattern is totally different. This confirms that the observed ion is in fact PM (16:0/20:4) and not PA (17:0/20:4)

Figure 5.

Figure 5.

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(a) MS/MS of mass peak at 661.48 in negative ion mode (CID 27%) compared with the (b) MS/MS of the PM (16:0/16:0) standard (CID 30%) (*interferences coming from ions isolated with the ion of interest).

Figure 6.

Figure 6.

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(a) MS/MS of mass peak at 709.48 in negative ion mode (CID 27%) compared with the (b) MS/MS of the PA (17:0sn1/20:4sn2) standard (CID 30%) (*interferences coming from ions isolated with the ion of interest).

All significant PA species are in fact PM or a mixture of PM species, with in one case of two PM and one PA with the same formula (Table S1). However, PM and other phosphatidylalcohols are not native lipid species. Rather, they are generated during the extraction process51 from glycerophospholipids. Indeed if not deactivated by heat, in the presence of alcohols, the phosphatidyltransferase activity of phospholipase D causes artifactual formation of non-native lipids such as PM.52,53 Even if the PM detected in this study are not directly biologically relevant (methanol was used during the extraction process), they give us interesting information about Phospholipase D activity. Indeed the production of such non-native lipids can serve as a marker of phospholipase D activity as previously described by Abdullaeva et al.54 These findings suggest that the phospholipase D activity decreases with alcohol consumption in adults.

CONCLUSION

It is common knowledge that chronic alcohol consumption can affect the brain. Alcohol abuse is considered a mental disorder characterized by a recurring use of alcohol despite its negative consequences. But even if effects of ethanol on the brain are well-known, the molecular mechanisms behind those neuronal disturbances remain unclear. Because lipids are major components of the brain and also important signaling molecules, it seemed relevant to investigate their implication in alcohol abuse. This study focused on the quantification of lipids with ethanol consumption in two rat age groups (juveniles and adults) and highlighted some interesting changes.

The first important observation is that alcohol seems to have opposite markedly different effect on lipid content in juvenile brain compared with adult brain. The maturation of the brain is a long process that is still occurring during adolescence, and the plasticity of juvenile brain could explain why the effects of alcohol seem less important in the juvenile group.

Significant changes were observed in different lipid classes including some sphingolipids (sphingomyelins and ceramides50), fatty acids, and lysophosphatidylcholines. Free fatty acids and lysophosphatidylcholines are both generated by phospholipase A2. Neuroinflammation and brain damage caused by chronic alcohol consumption or other neurodegenerative diseases have implicated phospholipase A2,55,56 including demyelination.57 Myelin membranes of brain are characterized by the presence of long-chain saturated and monounsaturated fatty acids especially nervonic (24:1) acid, which is a biomarker of myelin.58,59 Almost all of the significantly increased free fatty acids are long-chain saturated and monounsaturated fatty acids (with the exception of 22:4). Their increase with alcohol consumption suggests an increase of degradation of myelin lipids.60

Fatty acids can influence inflammation through a broad range of mechanisms. It is common knowledge that long-chain polyunsaturated fatty acids are involved in the inflammation process; eicosanoids derived from ω-6 polyunsaturated fatty like arachidonic acid (20:4 ω-6) are pro-inflammatory while ω-3 polyunsaturated fatty acids like eicosapentaenoic acid (20:5 ω-3) decrease the production of inflammatory eicosanoids.61 No changes in arachidonic acid or eicosapentaenoic acid were observed in this study; however a few free fatty acids showed significant increase with alcohol consumption in the adult group. They are all long or very-long chains fatty acids, saturated (20:0, 22:0) or monounsaturated (20:1, 22:1, 24:1) (with the exception of 22:4). Some studies show that fatty acids other than ω-6 FA can also activate an inflammatory response and neuronal stress. Long-chain saturated fatty acids, including arachidic (20:0) and behenic (22:0) (increased in study), induced the expression of inflammatory cytokines in the hypothalamus of mice and rats62,63 and cultured astrocytes.64

Lysophosphatidylcholines are involved in various physiologic and pathologic processes, including inflammation.65,66 They increase in tissues during ischemia67 and in plasma in rheumatoid arthritis,68 diabetes,69 and obesity.70 In the brain, it has been shown that lysophosphatidylcholines were released in neurons and astrocytes in the acute stage of ischemic stroke resulting in neuroinflammation and neuronal degeneration.71 Another important signaling pathway related to lysoPC involves phospholipase D (PLD).72,73 LysoPC stimulates phospholipase D by activation of phosphokinase C (PKC). PLD enzyme generates phosphatidic acid (PA) from phosphatidylcholine. Primary alcohols like ethanol are not a PLD inhibitor, but they block the enzyme by competing with water as a nucleophile. Thus, in the presence of ethanol, PLD synthesizes phosphatidylethanol (PEt) instead of PA, and in the presence of methanol, PLD synthesizes phosphatidylmethanol (PM). In this study, some PEt was detected but interfered with PA because they have very similar structure (for example, PEt 34:1 has the same molecular formula as PA 36:1). PM was detected and showed a significant decrease with alcohol consumption in adults. This finding suggests an apparent decrease in PLD activity in the brain, which is consistent with a previous study that found decreased PLD in rat pancreas from ethanol consumption.74

METHODS

Animals.

Male C57BL/6 mice were obtained from Taconic at 3 weeks (juvenile) or 6 weeks (adult) of age and allowed to habituate to the animal facility for 2 weeks. Weights were 13.81 ± 1.65 g for juveniles and 20.05 ± 1.50 g for adults before habituation. All mice were treated in accordance with IACUC guidelines. At 5 weeks of age for juveniles and 8 weeks of age for adults, mice were placed on a drinking-in-the-dark paradigm (DID).75,76 Briefly, all mice were split into either control (water) or ethanol (EtOH) group. The EtOH group had daily 4-h access to a 12% ethanol bottle during their dark cycle for 52 days. Control mice only had access to water for drinking. Food and water was given ad libitum for all mice at all times. Body weights at the start of the DID paradigm were 20.88 ± 1.42 g for juvenile water, 21.07 ± 1.55 g for juvenile EtOH, 22.34 ± 1.56 g for adult water, and 22.58 ± 1.62 g for adult EtOH. Drinking intake and body weight were measured daily for 52 days. The next day, mice were euthanized 1 h after ethanol access, and brain and liver tissues were collected. Wet liver weight was measured, and all tissue samples were flash frozen in 2-methylbutane on dry ice and stored at −80 °C until further processing. Body weight for each group on the final day was 29.68 ± 3.16 g for juvenile water, 29.78 ± 4.01 g for juvenile EtOH, 28.82 ± 2.54 g for adult water, and 29.94 ± 3.44 g for adult EtOH. Total cumulative EtOH intake was 108.36 ± 19.61 g/kg for the juvenile EtOH and 85.60 ± 16.38 g/kg for adult the EtOH groups. Statistics were performed on body weight (at the time of sacrifice), liver wet weight, and cumulative alcohol consumption. Body and liver weight did not show statistical differences among the 4 groups. However, cumulative alcohol consumption was significantly higher (+21% higher, unpaired t test p-value =0.0060) in the juvenile group compared with the adult group.

Lipid Extraction and Fractionation.

Total lipids are extracted from brain homogenate using a modified Folch extraction method. Brains were weighed and ground in a mixture of chloroform/methanol (2:1 v/v, 20 μL for each 1 mg tissue). Lipid standards were added to this total volume (the volume of lipid standards was subtracted from the total volume of chloroform/methanol) according the weight of each brain (see Table 1). Tissues were homogenized, sonicated, and vortexed. Water (4 μL for each 1 mg of tissue) was added. The mixture was again vortexed and centrifuged. The extraction results in an upper aqueous phase (enriched in ganglioside species) and a lower organic phase (containing lipids such as phospholipids, cerebrosides, and ceramides). The upper phase (aqueous phase) was removed and stored at −20 °C. The lower phase (organic phase) was evaporated to dryness using nitrogen, resuspended in chloroform (equal to the remaining volume of extraction liquid after lipid standard added), and fractionated. The fractionation was performed with SuperClean LC-NH2 SPE tubes, 1 mL (Sigma no. 504483). The columns were conditioned with 2 mL of hexane, and 200 μL of samples in chloroform was loaded on it. The fractions were retrieved using different solvents, and lipids contained in the resulting fractions are described in Table 1. Results from fractions 2−to 6 are discussed in this study; fraction 1 and aqueous phase were not analyzed.

Table 1.

Different Phases/Fractions for Lipids Extraction/Fractionation and Their Parameters

organic/lower phase
aqueous/upper phase fraction 1 fraction 2 fraction 3 fraction 4 fraction 5 fraction 6
lipids gangliosides DAG, TAG, cholesterol Cer, MAG free FA, modified FA cerebrosides, sphingoid bases SM, PC, PE ST, PS, PI, PG, CL, PA
fractionation na 2 mL diethyl ether 1.6 mL CHL/MeOH (23/1) 1.8 mL diisopropyl ether/acetic acid (98/4) 2 mL acetone/MeOH (9/1.2) 2 mL CHL/MeOH (2/1) 2 mL 0.2 M C2H4O2·NH3 MeOH
internal standards na na Cer C12:0/dl8:1 stearic acid d3 GalCer C12:0/d18:1 PC 14:0/14:0 PS 12:0/12:0
concentration/amount of internal standard na na 1 mg/mL 0.2 μL per mg of tissue 2 mg/mL 2 μL per mg of tissue 1 mg/mL 0.75 μL per mg of tissue 5 mg/mL 1 μL per mg of tissue 5 mg/mL 1.2 μL per mg of tissue
dilution for MS analysis na na 1/10 in MeOH 1/50 in MeOH 1/10 in MeOH 1/100 in C2H4O2·NH3 MeOH 1/10 in MeOH
ion mode na na NEG NEG NEG POS NEG
mass range na na 400–800 200–800 400–2000 400–1000 400–2000
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ESI Mass Spectrometric Analysis.

Samples were diluted and analyzed on an Oribtrap Velos (Thermo Fisher) with a static nanospray source with 4 μm spray tips and a capillary temperature of 200 °C. The FTMS mode with a mass resolution of 100 000 was employed for all samples. All fractions were analyzed in with a spray =1.5 kV, Rf = 69%, and 1 scan = 500 ms for the negative ion mode or 250 ms for the positive ion mode. For fraction 2, adducts were observed and removed or reduced by source fragmentation. MS/MS analyses were also conducted to confirm the identification of the annotated lipids. MS/MS were conducted on all detected lipids. However, not all MS/MS were conclusive for lipid structure assignments. Results of structural analysis are also available in Table S1. The same mass spectrometry parameters were used, and the CID energy ranged from 15% to 40%.

Data Processing and Statistical Analysis.

For each fraction, data were annotated according to our lipid database. Intensities for all annotated lipid in each sample were automatically reported in Excel (Microsoft Corporation, Redmond, WA) using R software77 (version 2.15.1). Data were normalized with the intensity of the internal standard of each fraction for relative quantification and analyzed by statistical analysis software. Data matrices were processed by multivariate analysis using the PLS toolbox (eigenvector Research Inc., version 6.7, Wenatchee, WA.) and MatLab software (MathWorks Inc., version R2012a, Natick, MA). This analysis allows visualization of the clustering of the samples and highlighting of the variables of interest (i.e., which variables are changing in each group of sample). Then, each variable of interest was investigated by univariate analysis (two-way ANOVA and Bonferroni posttests) using GraphPad Prism software (GraphPad Software Inc. version 5.00 for Windows, San Diego, CA). The two parameters used were the age (JUV/ADU) and alcohol consumption (H2O/EtOH)].

Supplementary Material

Table S1

ACKNOWLEDGMENTS

Ionwerks gratefully acknowledges partial support for this work from NIDA SBIR Phase II grants 5R44DA030853-04 and 5R44DA036263-04.

Footnotes

ASSOCIATED CONTENT

Supporting Information

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acschemneuro.6b00120.

List of all 380 lipids detected sorted by species and classes (XLSX)

The authors declare no competing financial interest.

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Supplementary Materials

Table S1
NIHMS1622995-supplement-Table_S1.xlsx (43.3KB, xlsx)

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