Transmembrane protein 135 (TMEM135) is thought to participate in the cellular response to increased intracellular lipids yet no defined molecular function for TMEM135 in lipid metabolism has been identified. In this study, we performed a lipid analysis of tissues from Tmem135 mutant mice and found striking reductions of docosahexaenoic acid (DHA) across all Tmem135 mutant tissues, indicating a role of TMEM135 in the production of DHA. Since all enzymes required for DHA synthesis remain intact in Tmem135 mutant mice, we hypothesized that TMEM135 is involved in the export of DHA from peroxisomes. The Tmem135 mutation likely leads to the retention of DHA in peroxisomes, causing DHA to be degraded within peroxisomes by their beta-oxidation machinery. This may lead to generation or alteration of ligands required for the activation of peroxisome proliferator-activated receptor a (PPARa) signaling, which in turn could result in increased peroxisomal number and beta-oxidation enzymes observed in Tmem135 mutant mice. We confirmed this effect of PPARa signaling by detecting decreased peroxisomes and their proteins upon genetic ablation of Ppara in Tmem135 mutant mice. Using Tmem135 mutant mice, we also validated the protective effect of increased peroxisomes and peroxisomal beta-oxidation on the metabolic disease phenotypes of leptin mutant mice which has been observed in previous studies. Thus, we conclude that TMEM135 has a role in lipid homeostasis through its function in peroxisomes.

Dataset was collected by the following methods:

Sample preparation for lipidomics analysis. Livers, retinas (neural retinas and eyecups), hearts, and plasmas were collected and stored at -80°C prior to lipid extraction. Prior to extraction, all solutions were pre-chilled on ice. Samples were transported and cut on a dry ice-cooled stainless steel plate and weighed on a Mettler (XSR205) analytical balance to the nearest hundredth of a milligram. This weight would be used to normalize samples for analysis. Fifty microliter aliquots of plasma from each mouse were used in this study. No normalization occurred with the plasma samples since the same volume for each sample was used in this study. Tissues were then placed into Qiagen PowerBead tubes (P/N 13113-50) for homogenization and extraction. Lipids were extracted in a solution of 250 µL PBS, 225 µL methanol containing internal standards (Avanti SPLASH LipidoMix (Lot#3307-07) at 10 µL per sample) and 750 µL MTBE (methyl tert-butyl ether). The samples were homogenized in three 30-second cycles alternated with a 5-minute rest on ice using a Qiagen TissueLyzer II operated at 30 Hz. The final rest on ice was 15 minutes. After centrifugation at 16,000 g for 5 minutes at 4°C, 500 µL of the upper phase was collected in 1.5 ml centrifuge tubes and evaporated to dryness in a Savant speedvac concentrator. Lipid samples were reconstituted in 150 µL of isopropanol.  A process blank was prepared in parallel with the tissue samples during extraction and analyzed concurrently with the samples. A pooled sample, used for lipid identification and quality control, was prepared by taking equal volumes from each sample of a given tissue after final resuspension in IPA.

LC-MS methods for lipidomics. Sample analysis was done at different dilution factors for different tissues and ionization polarities. For each injection samples were diluted in isopropanol by adding a given sample volume to isopropanol in an LC-MS vial with deactivated glass insert (Agilent P/N 5182-0554 and 5183-2086), vortexed to mix, and spun at low speed to collect the liquid prior to placing in the autosampler for analysis. Lipid extracts were separated on a Waters Acquity UPLC BEH C18 1.7 µm 2.1 x 100 mm column coupled in tandem with a Waters Acquity UPLC BEH C18 1.7 µm VanGaurd pre-column 2.1x5mm and maintained at 50°C. These columns in turn were connected to an Agilent HiP 1290 Multisampler, Agilent 1290 Infinity II binary pump, and column compartment connected to an Agilent 6546 Accurate Mass Q-TOF dual ESI mass spectrometer. For positive ion mode, the source gas temperature was set to 250°C, with a gas flow of 12 L/min and a nebulizer pressure of 35 psig. VCap voltage was set at 4000 V, fragmentor at 145 V, skimmer at 45 V and Octopole RF peak at 750 V. For negative ion mode, the source gas temperature was set to 350°C, with a drying gas flow of 12 L/min and a nebulizer pressure of 25 psig. VCap voltage is set at 5000 V, fragmentor at 200 V, skimmer at 45 V and Octopole RF peak at 750 V. Reference masses in positive mode (m/z 121.0509 and 922.0098) and negative mode (m/z 966.0007, and 112.9856) were delivered to the second emitter in the dual ESI source by isocratic pump at 15 uL/min. Samples were analyzed in a randomized order in both positive and negative ionization modes in separate experiments acquiring with the scan range m/z 100–1500. Mobile phase A consisted of acetonitrile:water (60:40 v/v) containing 10 mM ammonium formate and 0.1% formic acid, and mobile phase B consists of isopropanol: acetonitrile:water (90:9:1 v/v) containing 10 mM ammonium formate and 0.1% formic acid. The chromatography gradient for both positive and negative modes started at 15% mobile phase B then increases to 30% B over 2.4 min, then increased to 48% B from 2.4–3.0 min, then increased to 82% B from 3–13.2 min, then increased to 99% B from 13.2–13.8 min where it was held until 15.4 min and then returned to the initial conditions and equilibrated for 4 min. Flow was 0.5 mL/min throughout the gradient.  Injection volumes were 2 µL for positive mode and 5 µL for negative mode MS1 acquisitions, and 4 µL for positive mode and 7 µL for negative mode MS/MS acquisitions. Tandem mass spectrometry (MS/MS) was conducted using the same LC gradient as above with isolation width set to “narrow” (~1.3 m/z) and collision energy of 25 V. MS/MS data was collected on the pooled sample per tissue in iterative mode, in which the sample is analyzed 5 times with different precursors selected upon each injection. This permits access to lower-abundance lipid species in a background of highly abundant lipids.  

Dataset has been processed by the following methods:

Data Analysis. Pooled MS/MS and individual sample MS data were analyzed using a combination of Agilent and web-based applications. Lipid identification was achieved from the pooled MS/MS data via Lipid Annotator (Agilent). This software utilizes accurate mass m/z values for the intact lipid and experimental and theoretical fragment ion m/z values to assign lipid class and alkyl chain identities where possible. In some cases, specific alkyl chain identities cannot be assigned, but the sum composition of those alkyl chains (i.e. carbon number and degree of unsaturation) can be determined and that is reported instead. The output from Lipid Annotator is a database of lipid species with m/z values and retention times for each. This process was performed independently for positive and negative ion modes. Quantitation of lipids in individual samples used MS data alone. In this analysis, data for each sample was collected separately. The abundance of each lipid in each sample was tabulated using the Profinder application (Agilent). In this analysis, the database of lipid identity, m/z values (for protonated, deprotonated, ammonium or sodium adducted, or formate adducted, depending on ionization mode) and retention time was used to extract an ion chromatogram for each lipid species. These chromatograms were then integrated to produce an area for that lipid in each sample.  These abundance values were then exported as a .csv file for statistical analysis using the web-based tool MetaboAnalyst 5.0. This software was used for principal component analysis and statistical testing. The datasets provided in this depository are the .csv files for the MetaboAnalyst 5.0 program.

The programs required to open the data files include Microsoft Excel and MetaboAnalyst 5.0 (https://www.metaboanalyst.ca).