Literature DB >> 32021890

Lipidomics dataset of sonication-induced traumatic optic neuropathy in mice.

Ronaldo Nuesi1, Ryan A Gallo1, Galina Dvoriantchikova1, Daniel Pelaez1, Sanjoy K Bhattacharya1.   

Abstract

Traumatic optic neuropathy (TON) is the loss of vision secondary to trauma. Approximately two weeks after traumatic damage, diffuse retinal ganglion cell loss and axon degeneration of the optic nerve are exhibited [1]. Here we present the changes that occur in the optic nerve lipidome of two-month-old C57BL/6J mice following sonication-induced TON (SI-TON), which closely models the indirect clinical mechanism in TON. Optic nerves were harvested at three time points following injury: 1-day, 7-days, and 14-days for comparison with the control group (uninjured optic nerves from 2-month-old mice). The optic nerves were subjected to mass spectrometry and bioinformatic analysis using LipidSearch 4.1.3 and Metaboanalyst 4.0. This data pertains to the lipidome at each time point following indirect trauma to the optic nerve. The data presented here will augment investigation into the neurodegenerative process. The data is available at Metabolomics Workbench [http://www.metabolomicsworkbench.org (Project ID: PR000859)].
© 2020 The Authors.

Entities:  

Keywords:  Lipid profile; Liquid chromatography-mass spectrometry; Metabolomics; Neurodegeneration; Optic nerve injury; Traumatic optic neuropathy

Year:  2020        PMID: 32021890      PMCID: PMC6994518          DOI: 10.1016/j.dib.2020.105147

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications Table The data depicts changes in the optic nerve lipidome at post sonication injury time points compared to control pertinent to retinal ganglion cell loss (demonstrated previously) providing insight into lipid differences at the cellular level during injury induced axon degeneration. The data can be used to examine other optic neuropathies and broader neurodegeneration by investigators interested in changes at the cellular level following traumatic injuries. The data can serve as a template for specific lipid classes and species to assess behaviour of these lipids in the neurodegenerative process, for multi-omics studies and for providing information on these lipids that can be used to facilitate further experimentation utilizing specific species. This data will specifically serve as baseline changes in lipids in traumatic optic neuropathy model (induced using sonic wave) for pharmacological and biologics treatment. This data will also serve as potential lipidomics baseline for other traumatic injuries to optic nerve for comparative studies.

Data description

Here we present a lipid profiling of the optic nerve following sonication-induced trauma in two-month-old C57BL/6J mice and that from the control mice. Mice were placed in a sound-proof chamber and exposed to a 500msec sonic shock from a microtip probe as shown in Fig. 1. Optic nerve samples were collected at 1 day, 7 days, and 14 days post sonication and subjected to Methyl-Tert-Butyl Ether/Methanol (MTBE) lipid extraction. BCA Assay was used to aliquot lipids corresponding to a 30μg by protein in each sample. Lipids were re-suspended in Chloroform: Methanol (1:1) and processed through untargeted liquid chromatography Q-Exactive Orbitrap tandem mass spectrometry (LC-MS/MS). Relative quantification was performed using lipid peaks of the species identified with LipidSearch 4.1.3 software. Data from LipidSearch 4.1.3 was formatted and exported to Metaboanalyst 4.0 for statistical analyses as shown in Fig. 2. Labeling of samples were as in Table 1. A list of lipid nomenclature used can be found in Table 2 and identified lipids can be found in Supplementary Table S1.
Fig. 1

Schematic diagram of C57BL/6J mice exhibiting lipidomic changes following ultrasonicated ocular trauma. A probe was placed on the supraorbital rim and 500msec pulses were transmitted with 60–80 J of force. Mice optic nerves were harvested at one day, seven days, and fourteen days after sonic wave exposure. MTBE extraction was performed and lipids collected from the upper organic layer. Lipid changes in the optic nerve were analyzed using mass spectrometry and a heat map was generated.

Fig. 2

Lipidome heatmap. Relative abundance of lipid species with control (no exposure) and 1-day, 7-days and 14-days post exposure to sonication. All outliers were included and 56 significant species were identified by One Way ANOVA. (p-value set to 0.05).

Table 1

Sample Identification. 31 optic nerve samples were used from 15 males and 16 females. Each sample was run twice in positive mode and twice in negative mode.

SampleExposureDays Post ExposureSexESI Mode
C1No Sonication0MPos
C1No Sonication0MNeg
C2No Sonication0MPos
C2No Sonication0MNeg
C3No Sonication0MPos
C3No Sonication0MNeg
C4No Sonication0MPos
C4No Sonication0MNeg
C5No Sonication0FPos
C5No Sonication0FNeg
C6No Sonication0FPos
C6No Sonication0FNeg
C7No Sonication0FPos
C7No Sonication0FNeg
C8No Sonication0FPos
C8No Sonication0FNeg
D1_1Sonication1MPos
D1_1Sonication1MNeg
D1_2Sonication1MPos
D1_2Sonication1MNeg
D1_3Sonication1MPos
D1_3Sonication1MNeg
D1_4Sonication1MPos
D1_4Sonication1MNeg
D1_5Sonication1FPos
D1_5Sonication1FNeg
D1_6Sonication1FPos
D1_6Sonication1FNeg
D1_7Sonication1FPos
D1_7Sonication1FNeg
D1_8Sonication1FPos
D1_8Sonication1FNeg
D7_1Sonication7FPos
D7_1Sonication7FNeg
D7_2Sonication7FPos
D7_2Sonication7FNeg
D7_3Sonication7FPos
D7_3Sonication7FNeg
D7_4Sonication7FPos
D7_4Sonication7FNeg
D7_5Sonication7MPos
D7_5Sonication7MNeg
D7_6Sonication7MPos
D7_6Sonication7MNeg
D7_7Sonication7MPos
D7_7Sonication7MNeg
D14_1Sonication14MPos
D14_1Sonication14MNeg
D14_2Sonication14MPos
D14_2Sonication14MNeg
D14_3Sonication14MPos
D14_3Sonication14MNeg
D14_4Sonication14MPos
D14_4Sonication14MNeg
D14_5Sonication14FPos
D14_5Sonication14FNeg
D14_6Sonication14FPos
D14_6Sonication14FNeg
D14_7Sonication14FPos
D14_7Sonication14FNeg
D14_8Sonication14FPos
D14_8Sonication14FNeg
Table 2

LipidSearch nomenclature.

GroupAbbreviationsLipid Name
P-CholineLPClysophosphatidylcholine
PAFplatelet-activating factor
PCphosphatidylcholine
MePCMethyl phosphatidylcholine



P-Ethanol AmineLPElysophosphatidylethanolamine
LdMePElysodimethylphosphatidylethanolamine
PEphosphatidylethanolamine
BisMePEBis-methyl phosphatidylethanolamine
dMePEdimethylphosphatidylethanolamine



P-SerineLPSlysophosphatidylserine
PSphosphatidylserine
BisMePSBis-methyl phosphatidy lserine



P-GlycerolLPGlysophosphatidylglycerol
PGphosphatidylglycerol
BisMePGBis-methyl phosphatidylglycerol



P-InositolLPIlysophosphatidylinositol
PIphosphatidylinositol
PIPphosphatidylinositol
PIP2phosphatidylinositol
PIP3phosphatidylinositol



P-EthanolLPEtlysophosphatidylethanol
PEtphosphatidylethanol



P-AcidLPAlysophosphatidic acid
BisMeLPABis-methyl lysophosphatidic acid
PAphosphatidic acid
BisMePABis-methyl phosphatidic acid
cPAcyclic phosphatidic acid



P-MethanolLPMelysophosphatidylmethanol
PMephosphatidylmethanol



SphingolipidsSMsphingomyelin
LSMlysosphingomyelin
phSMsphingomyelin (phytosphingosine)



Neutral glycerolipidMGmonoglyceride
DGdiglyceride
TGtriglyceride



Fatty AcidFAfatty acid



CardiolipinCLCardiolipin



Sphingoid baseSoSphingosine
SoPSphingosine phosphate



Neutral GlycosphingolipidsSoG1Glucosylsphingosine
CerG1Simple Glc series
CerG2Simple Glc series
CerG3Simple Glc series
CerG2GNAc1Simple Glc series
CerG3GNAc1Simple Glc series
CerG3GNAc2Simple Glc series
STSulfatide



GlycosphingolipidsCerCeramides
CerPCeramides phosphate
GM3Gangliosides
GM2Gangliosides
GM1Gangliosides
GD1aGangliosides
GD1bGangliosides
GD2Gangliosides
GD3Gangliosides
GT1aGangliosides
GT1bGangliosides
GT1cGangliosides
GT2Gangliosides
GT3Gangliosides
GQ1cGangliosides
GQ1bGangliosides



SteroidChECholesterol Ester
ZyEzymosterol
StEStigmasterol ester
SiESitosterol ester
AGlcSiEAcylGlcSitosterol ester
D7ChEDeuterated Cholesterol Ester



CoenzymeCoCoenzyme



Fatty EsterOAHFA(O-acyl)-1-hydroxy fatty acid
WEwax exters
AcCaAcyl Carnitine



GlycoglycerolipidMGMGMonogalactosylmonoacylglycerol
MGDGMonogalactosyldiacylglycerol
DGMGDigalactosylmonoacylglycerol
DGDGDigalactosyldiacylglycerol
SQMGSulfoquinovosylmonoacylglycerol
SQDGSulfoquinovosyldiacylglycerol



Neutral glycerolipid (deuterated)D5DGDeuterated diglyceride
D5TGDeuterated triglyceride
Schematic diagram of C57BL/6J mice exhibiting lipidomic changes following ultrasonicated ocular trauma. A probe was placed on the supraorbital rim and 500msec pulses were transmitted with 60–80 J of force. Mice optic nerves were harvested at one day, seven days, and fourteen days after sonic wave exposure. MTBE extraction was performed and lipids collected from the upper organic layer. Lipid changes in the optic nerve were analyzed using mass spectrometry and a heat map was generated. Lipidome heatmap. Relative abundance of lipid species with control (no exposure) and 1-day, 7-days and 14-days post exposure to sonication. All outliers were included and 56 significant species were identified by One Way ANOVA. (p-value set to 0.05). Sample Identification. 31 optic nerve samples were used from 15 males and 16 females. Each sample was run twice in positive mode and twice in negative mode. LipidSearch nomenclature.

Experimental design, materials, and methods

Animals

All animals were treated in accordance with the Association for Research in Vision and Ophthalmology (ARVO) statement for the use of animals in ophthalmic and vision research, and were used under protocols approved by the University of Miami, Institutional Animal Care and Use Committee (IACUC). C57BL/6J mice were obtained from Jackson Laboratory (Bar Harbor, ME, USA). Mice were maintained in a temperature-regulated environment with a 12-h light, 12-h dark cycle, and all mice were fed ad libitum. Two-month-old mice were used for this dataset.

Sonication-induced traumatic optic neuropathy model

Sonication-induced traumatic optic neuropathy (SI-TON) model was performed as described previously [1]. Briefly, TON was induced in two-month-old C57BL/6J mice with a Branson Digital Sonifier 450 (Branson Ultrasonics, Danbury, CT, USA) by a 3mm microtip probe in an acoustic soundproof enclosure chamber. Mice were anesthetized with vaporized isoflurane supplied with oxygen in an induction chamber. The fur adjacent to each mouse's supraorbital rim was shaved, and each mouse was placed on the stage of a sound-proof enclosure equipped with an anesthesia mask for continuous supply of anesthesia. The stage was adjusted so that the microtip probe was in direct contact with the supraorbital rim above the insertion point of the optic nerve into the optic canal. Only left optic nerves were injured. The sonicator was programmed to deliver a 500 msec shock at a 35% or 40% amplitude, which results in a 230 to 250-μm oscillation according to the manufacturers' specifications. After sonication, mice were placed in a new cage with thermal support until fully recovered.

MTBE lipid extraction

Optic nerves were carefully dissected at 1 day, 7 days, and 14 days post exposure, beginning from the optic nerve head and continuing on until reaching the optic chiasm. Methyl-tert-butyl ether (MTBE) extraction was then performed as described with some modifications [2]. Briefly, optic nerves were immersed in 400 μl of Methanol + BHT then snap frozen and thawed for five-minute cycles using liquid nitrogen and a 37° water bath until completely homogenized. Samples were transferred to amber glass vials and 1.3 mL of MTBE was added. They were incubated in the dark at 4 °C on an orbital shaker overnight. The following day, samples were transferred to a centrifuge tube and 417 μl of 0.15 M Ammonium Acetate was added. They were then centrifuged for 10 min at 2000×g at 4 °C. The organic layer (upper) was collected, transferred to 2mL glass vials and dried in a centrifugal vacuum concentrator. Samples were re-suspended in 50 μl of 1:1 Chloroform: Methanol and stored in −20 °C until further processing.

High performance liquid chromatography and mass spectrometry

Lipids were analyzed by liquid chromatography electrospray tandem mass spectrometry (LC-MS/MS) using an Accela HPLC system and an orbitrap mass spectrometer (Q Exactive, Thermo Scientific, Waltham MA). An Acclaim 120 C18 3μm column (Thermo Scientific) was used with LC-MS grade Methanol: Water 60:40 v/v with 10mM Ammonium Acetate and Methanol Chloroform 60:40 v/v with 10mM Ammonium Acetate, as solvent A and B, respectively. A Heated Electrospray Ionization Source (HESI) was operated at a spray voltage of 4.4kV, a HESI vaporization temperature of 275 °C, a sheath gas pressure of 45 arbitrary units, and an auxillary gas flow of 15 arbitrary units. The ion transfer tube was kept at a temperature of 350 °C. The scan range was set at 150–1500 m/z. The gradient ran at 35%–100% Solvent B for 13 minutes and then was held at 35% solvent B for 2 minutes. The gradient was then brought up to 100% solvent A for 3 minutes and held for 2 minutes.

Lipid identification and relative quantification

Raw data from LC-MS was uploaded to LipidSearch 4.1.3 (Thermo Scientific). The search parameters were as follows: productsearch, precursor (5/5) ppm, intensity threshold 1.0%, M-Score 0.0. Quantitation and Toprank filter were turned on, Main node filters were set to Main Isomer Peaks, and ID quality was graded from A-D. All target classes were selected with the exception of fatty esters, glycoglycerolipids, and deuterated glycerolipids. All adducts in negative mode were selected, and all adducts in positive mode were selected with the exceptions of Li+, (CH3CH2)3NH +, and (CH3) 2NH2 +.

Data analysis

After peaks were identified, every sample was aligned to calculate the unassigned peaks. During alignment, lipid identification was filtered by grading from A-C. A few peaks in the following lipid classes of CerG1, PC, LPC, PE, TG, and ST were rejected as false positives and removed. Data was placed into four groups (Control, One day, Seven Days, Fourteen Days) and statistical analysis was performed with Metaboanalyst 4.0. No missing values were detected. Data was normalized to the reference group (control), log transformation was applied, and heat maps were then generated (Fig. 2).

Specifications Table

SubjectCell Biology
Specific subject areaLipids, cell membranes
Type of dataTableFigure
How data were acquiredLiquid Chromatography Q-Exactive Orbitrap Mass Spectrometry, LipidSearch 4.1.3, Metaboanalyst 4.0
Data formatRawAnalyzedFiltered
Parameters for data collectionOptic nerve, age, survival
Description of data collectionOptic nerves were dissected beginning at the optic nerve head and ending right before the optic chiasm, Methyl-Tert-Butyl Ether lipid extraction was performed, and lipids were analyzed with LC-MS/MS.
Data source locationBascom Palmer Eye Institute, Miller School of Medicine at University of Miami, Miami, FL 33136, USA
Data accessibilityRepository name: Metabolomics Workbench- Project ID: PR000859Data identification number: https://doi.org/10.21228/M8NH5VDirect URL to data: https://www.metabolomicsworkbench.org/data/DRCCMetadata.php?Mode=Project&ProjectID=PR000859
Related research articleTao, W. et al., A Novel Mouse Model of Traumatic Optic Neuropathy Using External Ultrasound Energy to Achieve Focal, Indirect Optic Nerve Injury. Sci Rep, 2017.7 (1): p. 11779.
Value of the Data

The data depicts changes in the optic nerve lipidome at post sonication injury time points compared to control pertinent to retinal ganglion cell loss (demonstrated previously) providing insight into lipid differences at the cellular level during injury induced axon degeneration.

The data can be used to examine other optic neuropathies and broader neurodegeneration by investigators interested in changes at the cellular level following traumatic injuries.

The data can serve as a template for specific lipid classes and species to assess behaviour of these lipids in the neurodegenerative process, for multi-omics studies and for providing information on these lipids that can be used to facilitate further experimentation utilizing specific species.

This data will specifically serve as baseline changes in lipids in traumatic optic neuropathy model (induced using sonic wave) for pharmacological and biologics treatment. This data will also serve as potential lipidomics baseline for other traumatic injuries to optic nerve for comparative studies.

  2 in total

1.  Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics.

Authors:  Vitali Matyash; Gerhard Liebisch; Teymuras V Kurzchalia; Andrej Shevchenko; Dominik Schwudke
Journal:  J Lipid Res       Date:  2008-02-16       Impact factor: 5.922

2.  A Novel Mouse Model of Traumatic Optic Neuropathy Using External Ultrasound Energy to Achieve Focal, Indirect Optic Nerve Injury.

Authors:  Wensi Tao; Galina Dvoriantchikova; Brian C Tse; Steven Pappas; Tsung-Han Chou; Manuel Tapia; Vittorio Porciatti; Dmitry Ivanov; David T Tse; Daniel Pelaez
Journal:  Sci Rep       Date:  2017-09-18       Impact factor: 4.379

  2 in total
  2 in total

Review 1.  Traumatic optic neuropathy: a review of current studies.

Authors:  Bin Chen; Hengsen Zhang; Qing Zhai; Huaipeng Li; Chunxia Wang; Yong Wang
Journal:  Neurosurg Rev       Date:  2022-01-16       Impact factor: 3.042

2.  Mitochondrial lipid profiling data of a traumatic optic neuropathy model.

Authors:  Ronaldo Nuesi; Ryan A Gallo; Sean D Meehan; John V Nahas; Galina Dvoriantchikova; Daniel Pelaez; Sanjoy K Bhattacharya
Journal:  Data Brief       Date:  2020-04-30
  2 in total

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