Summary of Study ST001637

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001047. The data can be accessed directly via it's Project DOI: 10.21228/M8C68D This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001637
Study TitleA Metabolome Atlas of the Aging Mouse Brain
Study SummaryThe mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remains poorly understood. To start bridging this gap, we generated a metabolome atlas of the aging mouse brain from 10 anatomical regions spanning from adolescence to late adulthood. We combined data from three chromatography-based mass spectrometry assays and structurally annotated 1,709 metabolites to reveal the underlying architecture of aging-induced changes in the brain metabolome. Overall differences between sexes were minimal. We found 94% of all metabolites to significantly differ between brain sections in at least one age group. We also discovered that 90% of the metabolome showed significant changes with respect to age groups. For example, we identified a shift in sphingolipid patterns during aging that is related to myelin remodeling in the transition from adolescent to adult brains. This shift was accompanied by large changes in overall signature in a range of other metabolic pathways. We found clear metabolic similarities in brain sections that were functionally related such as brain stem, cerebrum and cerebellum. In cerebrum, metabolic correlation patterns got markedly weaker in the transition from adolescent to ear adults, whereas correlation patterns between cerebrum and brainstem regions decreased from early to late adulthood. We were also able to map metabolic changes to gene and protein brain atlases to link molecular changes to metabolic brain phenotypes. Metabolic profiles can be investigated via https://atlas.metabolomics.us/. This new resource enables brain researchers to link new metabolomic studies to a foundation data set.
Institute
University of California, Davis
DepartmentGenome Center
LaboratoryWest Coast Metabolomics Center
Last NameDing
First NameJun
Address451 East Health Science Drive, Davis, CA, 95616, USA
Emailjunding@ucdavis.edu
Phone773-326-5420
Submit Date2020-12-23
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailGC-MS/LC-MS
Release Date2021-08-30
Release Version1
Jun Ding Jun Ding
https://dx.doi.org/10.21228/M8C68D
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001047
Project DOI:doi: 10.21228/M8C68D
Project Title:A Metabolome Atlas of the Aging Mouse Brain
Project Summary:The mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remains poorly understood. To start bridging this gap, we generated a metabolome atlas of the aging mouse brain from 10 anatomical regions spanning from adolescence to late adulthood. We combined data from three chromatography-based mass spectrometry assays and structurally annotated 1,709 metabolites to reveal the underlying architecture of aging-induced changes in the brain metabolome. Overall differences between sexes were minimal. We found 94% of all metabolites to significantly differ between brain sections in at least one age group. We also discovered that 90% of the metabolome showed significant changes with respect to age groups. For example, we identified a shift in sphingolipid patterns during aging that is related to myelin remodeling in the transition from adolescent to adult brains. This shift was accompanied by large changes in overall signature in a range of other metabolic pathways. We found clear metabolic similarities in brain sections that were functionally related such as brain stem, cerebrum and cerebellum. In cerebrum, metabolic correlation patterns got markedly weaker in the transition from adolescent to ear adults, whereas correlation patterns between cerebrum and brainstem regions decreased from early to late adulthood. We were also able to map metabolic changes to gene and protein brain atlases to link molecular changes to metabolic brain phenotypes. Metabolic profiles can be investigated via https://atlas.metabolomics.us/. This new resource enables brain researchers to link new metabolomic studies to a foundation data set.
Institute:University of California, Davis
Department:Genome Center
Laboratory:West Coast Metabolomics Center
Last Name:Ding
First Name:Jun
Address:451 East Health Science Drive, Davis, CA, 95616, USA
Email:junding@ucdavis.edu
Phone:773-326-5420
Funding Source:NIH U2C ES030158

Subject:

Subject ID:SU001714
Subject Type:Mammal
Subject Species:Mus musculus
Taxonomy ID:10090
Genotype Strain:C57BL/6NCrl
Age Or Age Range:3 weeks, 16 weeks and 59 weeks old
Gender:Male and female

Factors:

Subject type: Mammal; Subject species: Mus musculus (Factor headings shown in green)

mb_sample_id local_sample_id Brain region Age Gender
SA149974EA_F4_BGBasal ganglia 16 weeks Female
SA149975EA_F3_BGBasal ganglia 16 weeks Female
SA149976EA_F5_BGBasal ganglia 16 weeks Female
SA149977EA_F7_BGBasal ganglia 16 weeks Female
SA149978EA_F8_BGBasal ganglia 16 weeks Female
SA149979EA_F1_BGBasal ganglia 16 weeks Female
SA149980EA_F6_BGBasal ganglia 16 weeks Female
SA149981EA_F2_BGBasal ganglia 16 weeks Female
SA149982EA_M4_BGBasal ganglia 16 weeks Male
SA149983EA_M3_BGBasal ganglia 16 weeks Male
SA149984EA_M2_BGBasal ganglia 16 weeks Male
SA149985EA_M1_BGBasal ganglia 16 weeks Male
SA149986EA_M5_BGBasal ganglia 16 weeks Male
SA149987EA_M6_BGBasal ganglia 16 weeks Male
SA149988EA_M7_BGBasal ganglia 16 weeks Male
SA149989EA_M8_BGBasal ganglia 16 weeks Male
SA149990AD_F3_BGBasal ganglia 3 weeks Female
SA149991AD_F2_BGBasal ganglia 3 weeks Female
SA149992AD_F1_BGBasal ganglia 3 weeks Female
SA149993AD_F5_BGBasal ganglia 3 weeks Female
SA149994AD_F4_BGBasal ganglia 3 weeks Female
SA149995AD_F7_BGBasal ganglia 3 weeks Female
SA149996AD_F8_BGBasal ganglia 3 weeks Female
SA149997AD_F6_BGBasal ganglia 3 weeks Female
SA149998AD_M5_BGBasal ganglia 3 weeks Male
SA149999AD_M4_BGBasal ganglia 3 weeks Male
SA150000AD_M3_BGBasal ganglia 3 weeks Male
SA150001AD_M6_BGBasal ganglia 3 weeks Male
SA150002AD_M8_BGBasal ganglia 3 weeks Male
SA150003AD_M7_BGBasal ganglia 3 weeks Male
SA150004AD_M1_BGBasal ganglia 3 weeks Male
SA150005AD_M2_BGBasal ganglia 3 weeks Male
SA150006LA_F7_BGBasal ganglia 59 weeks Female
SA150007LA_F6_BGBasal ganglia 59 weeks Female
SA150008LA_F8_BGBasal ganglia 59 weeks Female
SA150009LA_F1_BGBasal ganglia 59 weeks Female
SA150010LA_F2_BGBasal ganglia 59 weeks Female
SA150011LA_F3_BGBasal ganglia 59 weeks Female
SA150012LA_F5_BGBasal ganglia 59 weeks Female
SA150013LA_F4_BGBasal ganglia 59 weeks Female
SA150014LA_M6_BGBasal ganglia 59 weeks Male
SA150015LA_M8_BGBasal ganglia 59 weeks Male
SA150016LA_M5_BGBasal ganglia 59 weeks Male
SA150017LA_M7_BGBasal ganglia 59 weeks Male
SA150018LA_M4_BGBasal ganglia 59 weeks Male
SA150019LA_M2_BGBasal ganglia 59 weeks Male
SA150020LA_M1_BGBasal ganglia 59 weeks Male
SA150021LA_M3_BGBasal ganglia 59 weeks Male
SA150022EA_F5_CBCerebellum 16 weeks Female
SA150023EA_F6_CBCerebellum 16 weeks Female
SA150024EA_F7_CBCerebellum 16 weeks Female
SA150025EA_F4_CBCerebellum 16 weeks Female
SA150026EA_F3_CBCerebellum 16 weeks Female
SA150027EA_F2_CBCerebellum 16 weeks Female
SA150028EA_F8_CBCerebellum 16 weeks Female
SA150029EA_F1_CBCerebellum 16 weeks Female
SA150030EA_M8_CBCerebellum 16 weeks Male
SA150031EA_M6_CBCerebellum 16 weeks Male
SA150032EA_M7_CBCerebellum 16 weeks Male
SA150033EA_M5_CBCerebellum 16 weeks Male
SA150034EA_M4_CBCerebellum 16 weeks Male
SA150035EA_M2_CBCerebellum 16 weeks Male
SA150036EA_M3_CBCerebellum 16 weeks Male
SA150037EA_M1_CBCerebellum 16 weeks Male
SA150038AD_F8_CBCerebellum 3 weeks Female
SA150039AD_F6_CBCerebellum 3 weeks Female
SA150040AD_F7_CBCerebellum 3 weeks Female
SA150041AD_F5_CBCerebellum 3 weeks Female
SA150042AD_F3_CBCerebellum 3 weeks Female
SA150043AD_F2_CBCerebellum 3 weeks Female
SA150044AD_F1_CBCerebellum 3 weeks Female
SA150045AD_F4_CBCerebellum 3 weeks Female
SA150046AD_M6_CBCerebellum 3 weeks Male
SA150047AD_M8_CBCerebellum 3 weeks Male
SA150048AD_M1_CBCerebellum 3 weeks Male
SA150049AD_M5_CBCerebellum 3 weeks Male
SA150050AD_M7_CBCerebellum 3 weeks Male
SA150051AD_M2_CBCerebellum 3 weeks Male
SA150052AD_M3_CBCerebellum 3 weeks Male
SA150053AD_M4_CBCerebellum 3 weeks Male
SA150054LA_F7_CBCerebellum 59 weeks Female
SA150055LA_F8_CBCerebellum 59 weeks Female
SA150056LA_F6_CBCerebellum 59 weeks Female
SA150057LA_F3_CBCerebellum 59 weeks Female
SA150058LA_F5_CBCerebellum 59 weeks Female
SA150059LA_F2_CBCerebellum 59 weeks Female
SA150060LA_F1_CBCerebellum 59 weeks Female
SA150061LA_F4_CBCerebellum 59 weeks Female
SA150062LA_M7_CBCerebellum 59 weeks Male
SA150063LA_M6_CBCerebellum 59 weeks Male
SA150064LA_M8_CBCerebellum 59 weeks Male
SA150065LA_M1_CBCerebellum 59 weeks Male
SA150066LA_M5_CBCerebellum 59 weeks Male
SA150067LA_M3_CBCerebellum 59 weeks Male
SA150068LA_M2_CBCerebellum 59 weeks Male
SA150069LA_M4_CBCerebellum 59 weeks Male
SA150070EA_F6_CTCerebral cortex 16 weeks Female
SA150071EA_F7_CTCerebral cortex 16 weeks Female
SA150072EA_F5_CTCerebral cortex 16 weeks Female
SA150073EA_F2_CTCerebral cortex 16 weeks Female
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Collection:

Collection ID:CO001707
Collection Summary:Brain tissue samples were collected from 3 weeks, 16 weeks and 59 weeks old male and female wild type mice on a C57BL/6NCrl background and performed under approved institutional IACUC protocols. Briefly, mice were anesthetized with 4% Isoflurane in 100% oxygen at a flow rate of 3 L/h to a surgical plane. Blood was then collected by retro-orbital bleed into an EDTA tube and centrifuged at 3000 rpm for 15 min to separate and remove plasma. While under anesthsia mice were perfused for approximately 10 minutes with phosphate buffered saline (PBS) pH 7.4 at room temperature. Following perfusion, the brain was removed and placed in a petri dish containing PBS at 4oC for dissection of individual brain regions. A dissection microscope, fine tip (#5) forceps, and razor blade was used to isolate and separate brain regions (olfactory bulb, hippocampus, hypothalamus, thalamus, midbrain, cerebellum, pons, medulla, cerebral cortex, and basal ganglia collected as caudate putamen and basal forebrain) in induvial mice while being careful to avoid contamination from neighboring regions. Briefly, after separating the olfactory bulbs, the left and right cerebral cortices were then removed while taking care not to disrupt the regions underneath. This enabled access to and removal of the left and right hippocampus. After cutting along the thalamus, the left and right caudate putamen was separated and removed from the basal forebrain. Subsequently, the cerebellum and midbrain were isolated and removed, followed by separation and removal of the thalamus and the hypothalamus from the pons and medulla. The pons was then separated from the medulla. Any spinal cord remaining on the medulla was removed. Each region was immediately placed in a cryo vial and flash frozen in liquid nitrogen for analysis.
Sample Type:Brain

Treatment:

Treatment ID:TR001727
Treatment Summary:Five milligrams of tissue from each brain region were homogenized in 225 µL of -20oC cold, internal standard-containing methanol using a GenoGrinder 2010 (SPEX SamplePrep) for 2 min at 1,350 rpm. The homogenate was vortexed for 10 s. 750 µL of -20oC cold, internal standard-containing methyl tertiary-butyl ether (MTBE) was added, and the mixture was vortexed for 10 s and shaken at 4 oC for 5 min with an Orbital Mixing Chilling/Heating Plate (Torrey Pines Scientific Instruments). MTBE contained cholesteryl ester 22:1 as internal standard. Next, 188 µL room temperature water was added and vortexed for 20 s to induce phase separation. After centrifugation for 2 min at 14,000 g, two 350 µL aliquots of the upper non-polar phase and two 125 µL aliquots of the bottom polar phase were collected and dried down. Remaining fractions were combined to form QC pools and were injected after every set of 10 biological samples. The non-polar phase employed for lipidomics was resuspended in a mixture of methanol/toluene (60 µL, 9:1, v/v) containing an internal standard [12-[(cyclohexylamino) carbonyl]amino]-dodecanoic acid (CUDA)] before injection. Resuspension of dried polar phases for HILIC analysis was performed in a mixture of internal standard-containing acetonitrile/water (90 µL, 4:1, v/v). The second dried polar phase was reserved for GC analysis and a following derivatization process was carried out before injection. First, carbonyl groups were protected by methoximation with methoxyamine hydrochloride in pyridine (40 mg/mL, 10 µL) was added to the dried samples. Then, the mixture was incubated at 30˚C for 90 min followed by trimethylsilylation with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA, 90 μL) containing C8–C30 fatty acid methyl esters (FAMEs) as internal standards by shaking at 37˚C for 30 min.

Sample Preparation:

Sampleprep ID:SP001720
Sampleprep Summary:Five milligrams of tissue from each brain region were homogenized in 225 µL of -20oC cold, internal standard-containing methanol using a GenoGrinder 2010 (SPEX SamplePrep) for 2 min at 1,350 rpm. The homogenate was vortexed for 10 s. 750 µL of -20oC cold, internal standard-containing methyl tertiary-butyl ether (MTBE) was added, and the mixture was vortexed for 10 s and shaken at 4 oC for 5 min with an Orbital Mixing Chilling/Heating Plate (Torrey Pines Scientific Instruments). MTBE contained cholesteryl ester 22:1 as internal standard. Next, 188 µL room temperature water was added and vortexed for 20 s to induce phase separation. After centrifugation for 2 min at 14,000 g, two 350 µL aliquots of the upper non-polar phase and two 125 µL aliquots of the bottom polar phase were collected and dried down. Remaining fractions were combined to form QC pools and were injected after every set of 10 biological samples. The non-polar phase employed for lipidomics was resuspended in a mixture of methanol/toluene (60 µL, 9:1, v/v) containing an internal standard [12-[(cyclohexylamino) carbonyl]amino]-dodecanoic acid (CUDA)] before injection. Resuspension of dried polar phases for HILIC analysis was performed in a mixture of internal standard-containing acetonitrile/water (90 µL, 4:1, v/v). The second dried polar phase was reserved for GC analysis and a following derivatization process was carried out before injection. First, carbonyl groups were protected by methoximation with methoxyamine hydrochloride in pyridine (40 mg/mL, 10 µL) was added to the dried samples. Then, the mixture was incubated at 30˚C for 90 min followed by trimethylsilylation with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA, 90 μL) containing C8–C30 fatty acid methyl esters (FAMEs) as internal standards by shaking at 37˚C for 30 min.

Combined analysis:

Analysis ID AN002675 AN002676 AN002677 AN002678 AN002679
Analysis type MS MS MS MS MS
Chromatography type HILIC HILIC Reversed phase Reversed phase GC
Chromatography system Thermo Vanquish Thermo Vanquish Thermo Vanquish Thermo Vanquish Agilent 6890N
Column Waters XBridge Amide (100 x 4.6mm,3.5um) Waters XBridge Amide (100 x 4.6mm,3.5um) Waters Acquity CSH C18 (100 x 2.1mm,1.7um) Waters Acquity CSH C18 (100 x 2.1mm,1.7um) Restek Rtx-5Sil (30m x 0.25mm,0.25um)
MS Type ESI ESI ESI ESI EI
MS instrument type Orbitrap LTQ-FT Orbitrap Ion trap GC-TOF
MS instrument name Thermo Q Exactive HF hybrid Orbitrap Thermo Q Exactive HF hybrid Orbitrap Thermo Q Exactive HF hybrid Orbitrap Thermo Q Exactive HF hybrid Orbitrap Leco Pegasus IV TOF
Ion Mode POSITIVE NEGATIVE POSITIVE NEGATIVE POSITIVE
Units Peak height Peak height Peak height Peak height Peak height

Chromatography:

Chromatography ID:CH001969
Chromatography Summary:HILIC positive
Instrument Name:Thermo Vanquish
Column Name:Waters XBridge Amide (100 x 4.6mm,3.5um)
Chromatography Type:HILIC
  
Chromatography ID:CH001970
Chromatography Summary:HILIC negative
Instrument Name:Thermo Vanquish
Column Name:Waters XBridge Amide (100 x 4.6mm,3.5um)
Chromatography Type:HILIC
  
Chromatography ID:CH001971
Chromatography Summary:CSH positive
Instrument Name:Thermo Vanquish
Column Name:Waters Acquity CSH C18 (100 x 2.1mm,1.7um)
Chromatography Type:Reversed phase
  
Chromatography ID:CH001972
Chromatography Summary:CSH negative
Instrument Name:Thermo Vanquish
Column Name:Waters Acquity CSH C18 (100 x 2.1mm,1.7um)
Chromatography Type:Reversed phase
  
Chromatography ID:CH001973
Chromatography Summary:GC
Instrument Name:Agilent 6890N
Column Name:Restek Rtx-5Sil (30m x 0.25mm,0.25um)
Chromatography Type:GC

MS:

MS ID:MS002474
Analysis ID:AN002675
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:The ion source conditions were set as follows: spray voltage, 3.6 kV; sheath gas flow rate, 60 arbitrary units; aux gas flow rate, 25 arbitrary units; sweep gas flow rate, 2 arbitrary units; capillary temp, 300 °C; S-lens RF level, 50; Aux gas heater temp, 370 °C. The following acquisition parameters were used for MS1 analysis: resolution, 60000, AGC target, 1e6; Maximum IT, 100 ms; scan range 60-900 m/z; spectrum data type, centroid. Data dependent MS/MS parameters: resolution, 15000; AGC target, 1e5; maximum IT, 50 ms; loop count, 4; TopN, 4; isolation window, 1.0 m/z; fixed first mass, 70.0 m/z; (N)CE/ stepped nce, 20, 30, 40; spectrum data type, centroid; minimum AGC target, 8e3; intensity threshold, 1.6e5; exclude isotopes, on; dynamic exclusion, 3.0 s. To increase the total number of MS/MS spectra, five runs with iterative MS/MS exclusions were performed using the R package “IE-Omics”18 for both positive and negative electrospray conditions. All the LC-MS raw data files were converted into ABF format using ABF converter (https://www.reifycs.com/AbfConverter/). MS-DIAL ver.4.00 software was used for deconvolution, peak picking, alignment, and compound identification19. The detailed parameter setting was as follows: MS1 tolerance, 0.005 Da; MS2 tolerance, 0.01 Da; minimum peak height, 20000 amplitude; mass slice width, 0.1 Da; smoothing method, linear weighted moving average; smoothing level, 5 scans; minimum peak width, 10 scans. [M+H]+, [M+NH4]+, [M+Na]+, [2M+H]+,[2M+NH4]+, [2M+Na]+ were included in adduct ion setting for positive mode lipidomics and HILIC analysis, [M-H]-, [M+Cl]-, [M+Hac-H]- for negative mode lipidomics, and [M-H]-, [M+Cl]-, [M+FA-H]-, [2M-H]- for negative mode HILIC analysis. Compounds were annotated by matching retention times, accurate precursor masses and MS/MS spectra against libraries in MassBank of North America and NIST17. Retention time libraries were produced from authentic standards and extrapolated for lipids as published before. The primary result data matrix was processed with MS-FLO software to identify ion adducts, duplicate peaks, and isotopic features. Systematic error removal by random forest (SERRF software) was employed to correct for batch effects or instrument signal drifts. Statistical analysis was performed by normalization to the median intensity of all identified compounds, log transformation and Pareto scaling. PCA was used for multivariate statistics and visualization, specifically for outlier detection. Two outliers, including one medulla sample from a female early adult and one basal ganglia sample from a female late adult, were removed. Results from Kruskal-Wallis tests were followed by Dunn’s multiple comparison confinement. Results from Mann–Whitney U tests were corrected by the Benjamini–Hochberg procedure to control the false discovery rate. Spearman rank correlation analyses and fold change calculations were conducted using R.
Ion Mode:POSITIVE
  
MS ID:MS002475
Analysis ID:AN002676
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:LTQ-FT
MS Type:ESI
MS Comments:The ion source conditions were set as follows: spray voltage, -3.0 kV; sheath gas flow rate, 60 arbitrary units; aux gas flow rate, 25 arbitrary units; sweep gas flow rate, 2 arbitrary units; capillary temp, 300 °C; S-lens RF level, 50; Aux gas heater temp, 370 °C. The following acquisition parameters were used for MS1 analysis: resolution, 60000, AGC target, 1e6; Maximum IT, 100 ms; scan range 60-900 m/z; spectrum data type, centroid. Data dependent MS/MS parameters: resolution, 15000; AGC target, 1e5; maximum IT, 50 ms; loop count, 4; TopN, 4; isolation window, 1.0 m/z; fixed first mass, 70.0 m/z; (N)CE/ stepped nce, 20, 30, 40; spectrum data type, centroid; minimum AGC target, 8e3; intensity threshold, 1.6e5; exclude isotopes, on; dynamic exclusion, 3.0 s. To increase the total number of MS/MS spectra, five runs with iterative MS/MS exclusions were performed using the R package “IE-Omics”18 for both positive and negative electrospray conditions. All the LC-MS raw data files were converted into ABF format using ABF converter (https://www.reifycs.com/AbfConverter/). MS-DIAL ver.4.00 software was used for deconvolution, peak picking, alignment, and compound identification19. The detailed parameter setting was as follows: MS1 tolerance, 0.005 Da; MS2 tolerance, 0.01 Da; minimum peak height, 20000 amplitude; mass slice width, 0.1 Da; smoothing method, linear weighted moving average; smoothing level, 5 scans; minimum peak width, 10 scans. [M+H]+, [M+NH4]+, [M+Na]+, [2M+H]+,[2M+NH4]+, [2M+Na]+ were included in adduct ion setting for positive mode lipidomics and HILIC analysis, [M-H]-, [M+Cl]-, [M+Hac-H]- for negative mode lipidomics, and [M-H]-, [M+Cl]-, [M+FA-H]-, [2M-H]- for negative mode HILIC analysis. Compounds were annotated by matching retention times, accurate precursor masses and MS/MS spectra against libraries in MassBank of North America and NIST17. Retention time libraries were produced from authentic standards and extrapolated for lipids as published before. The primary result data matrix was processed with MS-FLO software to identify ion adducts, duplicate peaks, and isotopic features. Systematic error removal by random forest (SERRF software) was employed to correct for batch effects or instrument signal drifts. Statistical analysis was performed by normalization to the median intensity of all identified compounds, log transformation and Pareto scaling. PCA was used for multivariate statistics and visualization, specifically for outlier detection. Two outliers, including one medulla sample from a female early adult and one basal ganglia sample from a female late adult, were removed. Results from Kruskal-Wallis tests were followed by Dunn’s multiple comparison confinement. Results from Mann–Whitney U tests were corrected by the Benjamini–Hochberg procedure to control the false discovery rate. Spearman rank correlation analyses and fold change calculations were conducted using R.
Ion Mode:NEGATIVE
  
MS ID:MS002476
Analysis ID:AN002677
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:The ion source conditions were set as follows: spray voltage, 3.6 kV; sheath gas flow rate, 60 arbitrary units; aux gas flow rate, 25 arbitrary units; sweep gas flow rate, 2 arbitrary units; capillary temp, 300 °C; S-lens RF level, 50; Aux gas heater temp, 370 °C. The following acquisition parameters were used for MS1 analysis: resolution, 60000, AGC target, 1e6; Maximum IT, 100 ms; scan range 150-1700 m/z; spectrum data type, centroid. Data dependent MS/MS parameters: resolution, 15000; AGC target, 1e5; maximum IT, 50 ms; loop count, 4; TopN, 4; isolation window, 1.0 m/z; fixed first mass, 70.0 m/z; (N)CE/ stepped nce, 20, 30, 40; spectrum data type, centroid; minimum AGC target, 8e3; intensity threshold, 1.6e5; exclude isotopes, on; dynamic exclusion, 3.0 s. To increase the total number of MS/MS spectra, five runs with iterative MS/MS exclusions were performed using the R package “IE-Omics”18 for both positive and negative electrospray conditions. All the LC-MS raw data files were converted into ABF format using ABF converter (https://www.reifycs.com/AbfConverter/). MS-DIAL ver.4.00 software was used for deconvolution, peak picking, alignment, and compound identification19. The detailed parameter setting was as follows: MS1 tolerance, 0.005 Da; MS2 tolerance, 0.01 Da; minimum peak height, 20000 amplitude; mass slice width, 0.1 Da; smoothing method, linear weighted moving average; smoothing level, 5 scans; minimum peak width, 10 scans. [M+H]+, [M+NH4]+, [M+Na]+, [2M+H]+,[2M+NH4]+, [2M+Na]+ were included in adduct ion setting for positive mode lipidomics and HILIC analysis, [M-H]-, [M+Cl]-, [M+Hac-H]- for negative mode lipidomics, and [M-H]-, [M+Cl]-, [M+FA-H]-, [2M-H]- for negative mode HILIC analysis. Compounds were annotated by matching retention times, accurate precursor masses and MS/MS spectra against libraries in MassBank of North America and NIST17. Retention time libraries were produced from authentic standards and extrapolated for lipids as published before. The primary result data matrix was processed with MS-FLO software to identify ion adducts, duplicate peaks, and isotopic features. Systematic error removal by random forest (SERRF software) was employed to correct for batch effects or instrument signal drifts. Statistical analysis was performed by normalization to the median intensity of all identified compounds, log transformation and Pareto scaling. PCA was used for multivariate statistics and visualization, specifically for outlier detection. Two outliers, including one medulla sample from a female early adult and one basal ganglia sample from a female late adult, were removed. Results from Kruskal-Wallis tests were followed by Dunn’s multiple comparison confinement. Results from Mann–Whitney U tests were corrected by the Benjamini–Hochberg procedure to control the false discovery rate. Spearman rank correlation analyses and fold change calculations were conducted using R.
Ion Mode:POSITIVE
  
MS ID:MS002477
Analysis ID:AN002678
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:Ion trap
MS Type:ESI
MS Comments:The ion source conditions were set as follows: spray voltage, -3.0 kV; sheath gas flow rate, 60 arbitrary units; aux gas flow rate, 25 arbitrary units; sweep gas flow rate, 2 arbitrary units; capillary temp, 300 °C; S-lens RF level, 50; Aux gas heater temp, 370 °C. The following acquisition parameters were used for MS1 analysis: resolution, 60000, AGC target, 1e6; Maximum IT, 100 ms; scan range 150-1700 m/z; spectrum data type, centroid. Data dependent MS/MS parameters: resolution, 15000; AGC target, 1e5; maximum IT, 50 ms; loop count, 4; TopN, 4; isolation window, 1.0 m/z; fixed first mass, 70.0 m/z; (N)CE/ stepped nce, 20, 30, 40; spectrum data type, centroid; minimum AGC target, 8e3; intensity threshold, 1.6e5; exclude isotopes, on; dynamic exclusion, 3.0 s. To increase the total number of MS/MS spectra, five runs with iterative MS/MS exclusions were performed using the R package “IE-Omics”18 for both positive and negative electrospray conditions. All the LC-MS raw data files were converted into ABF format using ABF converter (https://www.reifycs.com/AbfConverter/). MS-DIAL ver.4.00 software was used for deconvolution, peak picking, alignment, and compound identification19. The detailed parameter setting was as follows: MS1 tolerance, 0.005 Da; MS2 tolerance, 0.01 Da; minimum peak height, 20000 amplitude; mass slice width, 0.1 Da; smoothing method, linear weighted moving average; smoothing level, 5 scans; minimum peak width, 10 scans. [M+H]+, [M+NH4]+, [M+Na]+, [2M+H]+,[2M+NH4]+, [2M+Na]+ were included in adduct ion setting for positive mode lipidomics and HILIC analysis, [M-H]-, [M+Cl]-, [M+Hac-H]- for negative mode lipidomics, and [M-H]-, [M+Cl]-, [M+FA-H]-, [2M-H]- for negative mode HILIC analysis. Compounds were annotated by matching retention times, accurate precursor masses and MS/MS spectra against libraries in MassBank of North America and NIST17. Retention time libraries were produced from authentic standards and extrapolated for lipids as published before. The primary result data matrix was processed with MS-FLO software to identify ion adducts, duplicate peaks, and isotopic features. Systematic error removal by random forest (SERRF software) was employed to correct for batch effects or instrument signal drifts. Statistical analysis was performed by normalization to the median intensity of all identified compounds, log transformation and Pareto scaling. PCA was used for multivariate statistics and visualization, specifically for outlier detection. Two outliers, including one medulla sample from a female early adult and one basal ganglia sample from a female late adult, were removed. Results from Kruskal-Wallis tests were followed by Dunn’s multiple comparison confinement. Results from Mann–Whitney U tests were corrected by the Benjamini–Hochberg procedure to control the false discovery rate. Spearman rank correlation analyses and fold change calculations were conducted using R.
Ion Mode:NEGATIVE
  
MS ID:MS002478
Analysis ID:AN002679
Instrument Name:Leco Pegasus IV TOF
Instrument Type:GC-TOF
MS Type:EI
MS Comments:0.5 μL sample was injected with 25 s splitless time on an Agilent 6890 GC (Agilent Technologies, Santa Clara, CA) using a Restek Rtx-5Sil MS column (30 m x 0.25 mm, 0.25 μm) with 10 m Guard column (10 m x 0.25 mm, 0.25 μm) and 1 mL/min Helium gas flow. Oven temperature was held 50°C for 1 min, ramped up to 330 °C at 20 °C/min and held for 5 min. Data was acquired at 70 eV electron ionization at 17 spectra/s from 85 to 500 Da at 1850 V detector voltage on a Leco Pegasus IV time-of-flight mass spectrometer (Leco Corporation, St. Joseph, MI). The transfer line temperature was held at 280 °C with an ion source temperature set at 250 °C. Standard metabolites mixtures and blank samples were injected at the beginning of the run and every ten samples throughout the run for quality control. Raw data was preprocessed by ChromaTOF version 4.50 for baseline subtraction, deconvolution and peak detection. Binbase was used for metabolite annotation and reporting.
Ion Mode:POSITIVE
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