{
"METABOLOMICS WORKBENCH":{"STUDY_ID":"ST001702","ANALYSIS_ID":"AN002773","VERSION":"1","CREATED_ON":"February 17, 2021, 9:25 am"},

"PROJECT":{"PROJECT_TITLE":"A cross-sectional study of functional and metabolic changes during aging through the lifespan in male mice","PROJECT_TYPE":"Untargeted metabolomics","PROJECT_SUMMARY":"Aging is associated with distinct phenotypical, physiological, and functional changes, leading to the onset of disease and death. The progression of aging-related traits varies widely among individuals, influenced by their environment, lifestyle, and genetics. In this study, we performed physiologic and functional tests cross-sectionally throughout the entire lifespan of male C57BL/6N mice. In parallel, metabolomics analyses in serum, brain, liver, heart, and skeletal muscle were also performed to identify signatures associated with frailty and age-dependent functional decline. Our findings indicate that the decline in gait speed as a function of age and frailty is associated with dramatic increases in the energetic cost of physical activity and decreases in working capacity. Aging and functional decline prompt organs to rewire their substrate selection and metabolism towards redox-related pathways, mainly in liver and heart. Collectively, the data provide a framework to further understand and characterize processes of aging at the individual and organ levels.","INSTITUTE":"National Institutes of Health","DEPARTMENT":"Experimental Gerontology Section and Translational Gerontology Branch","LABORATORY":"NIA","LAST_NAME":"de Cabo","FIRST_NAME":"Rafael","ADDRESS":"251 Bayview Blvd. Suite 100/Room 5C214. Baltimore, MD 21224","EMAIL":"deCaboRa@grc.nia.nih.gov","PHONE":"1-410-558-8510","FUNDING_SOURCE":"Intramural Research Program of the National Institute on Aging, NIH"},

"STUDY":{"STUDY_TITLE":"A cross-sectional study of functional and metabolic changes during aging through the lifespan in male mice (Heart) part-IV","STUDY_SUMMARY":"Aging is associated with distinct phenotypical, physiological, and functional changes, leading to the onset of disease and death. The progression of aging-related traits varies widely among individuals, influenced by their environment, lifestyle, and genetics. In this study, we performed physiologic and functional tests cross-sectionally throughout the entire lifespan of male C57BL/6N mice. In parallel, metabolomics analyses in serum, brain, liver, heart, and skeletal muscle were also performed to identify signatures associated with frailty and age-dependent functional decline. Our findings indicate that the decline in gait speed as a function of age and frailty is associated with dramatic increases in the energetic cost of physical activity and decreases in working capacity. Aging and functional decline prompt organs to rewire their substrate selection and metabolism towards redox-related pathways, mainly in liver and heart. Collectively, the data provide a framework to further understand and characterize processes of aging at the individual and organ levels.","INSTITUTE":"National Institutes of Health","DEPARTMENT":"NIA","LABORATORY":"Experimental Gerontology Section and Translational Gerontology Branch","LAST_NAME":"de Cabo","FIRST_NAME":"Rafael","ADDRESS":"251 Bayview Blvd. Suite 100/Room 5C214. Baltimore, MD 21224","EMAIL":"deCaboRa@grc.nia.nih.gov","PHONE":"1-410-558-8510"},

"SUBJECT":{"SUBJECT_TYPE":"Mammal","SUBJECT_SPECIES":"Mus musculus","TAXONOMY_ID":"10090"},
"SUBJECT_SAMPLE_FACTORS":[
{
"Subject ID":"-",
"Sample ID":"18_heart_018",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa01_3.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"22_heart_022",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa02_3.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"25_heart_025",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa03_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"13_heart_013",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa04_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"24_heart_024",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa05_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"23_heart_023",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa06_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"4_heart_004",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa07_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"5_heart_005",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa08_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"16_heart_016",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa09_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"7_heart_007",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa10_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"26_heart_026",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa11_3.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"17_heart_017",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa12_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"21_heart_021",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa13_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"1_heart_001",
"Factors":{"Age":"young"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa14_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"27_heart_027",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa15_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"8_heart_008",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa16_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"9_heart_009",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa17_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"6_heart_006",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa18_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"29_heart_029",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa19_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"15_heart_015",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa20_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"11_heart_011",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa21_3.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"19_heart_019",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa22_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"30_heart_030",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa23_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"20_heart_020",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa24_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"14_heart_014",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa25_1.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"3_heart_003",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa26_1.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"10_heart_010",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa27_2.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"2_heart_002",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa28_1.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"12_heart_012",
"Factors":{"Age":"mid age"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa29_1.cdf"}
},
{
"Subject ID":"-",
"Sample ID":"28_heart_028",
"Factors":{"Age":"old"},
"Additional sample data":{"RAW_FILE_NAME":"160329dngsa30_2.cdf"}
}
],
"COLLECTION":{"COLLECTION_SUMMARY":"Tissues were collected from perfused mouse and flash frozen in liquid nitrogen. Samples stored at -80 degrees.","SAMPLE_TYPE":"Heart"},

"TREATMENT":{"TREATMENT_SUMMARY":"Healthy mice are divided based on their ages. 3 groups are presented: - Young (n=12): <15 mo-old - Mid (n=7): 15 to 20 mo-old - Old (n=11): >20 mo-old"},

"SAMPLEPREP":{"SAMPLEPREP_SUMMARY":"Extraction of Mammalian Tissue Samples: Lungs/Muscle/Heart 1. References: Fiehn O, Kind T (2006) Metabolite profiling in blood plasma. In: Metabolomics: Methods and Protocols. Weckwerth W (ed.), Humana Press, Totowa NJ (in press) 2.Starting material: Mammalian tissue: Lung/Muscle/Heart: Whole tissue sample is prepared OR stein mill whole tissue sample and weigh 50mL aliquot. 3. Equipment: Centrifuge (Eppendorf 5415 D) Calibrated pipettes 1-200?l and 100-1000?l Eppendorf tubes 2ml, uncoloured (Cat. No. 022363204) Centrifuge tubes, various sizes, polypropylene Eppendorff Tabletop Centrifuge (Proteomics core Lab.) ThermoElectron Neslab RTE 740 cooling bath at –20°C MiniVortexer (VWR) Orbital Mixing Chilling/Heating Plate (Torrey Pines Scientific Instruments) Speed vacuum concentration system (Labconco Centrivap cold trap) Turex mini homogenizer 4. Chemicals Acetonitrile, LCMS grade (JT Baker; Cat. No.9829-02) Isopropanol, HPLC grade (JT Baker; Cat. No. 9095-02) Crushed ice pH paper 5-10 (EMD Chem. Inc.) Nitrogen line with pipette tip 18 M? pure water (Millipore) 5. Procedure Preparation of extraction mix and material before experiment: Switch on bath to pre-cool at –20°C (±2°C validity temperature range) Check pH of acetonitrile and isopropanol (pH7) using wetted pH paper Make the extraction solution by missing acetonitrile, isopropanol and water in proportions 3 : 3 : 2 Rinse the extraction solution for 5 min with nitrogen. Make sure that the nitrogen line was flushed out of air before using it for degassing the extraction solvent solution Sample Preparation Weigh 50 mg tissue sample in to a 25 ml conical polypropylene centrifuge tube. Add 2.5mL extraction solvent to the tissue sample and homogenize for 45 seconds ensuring that sample resembles a powder. In between samples, clean the homogenizer in solutions of methanol, acetone, water, and the extraction solvent. Centrifuge the samples at 2500 rpm. for 5 minutes. Aliquot 2 X 500µl supernatant, one for analysis and one for a backup sample. Store backup aliquot in the -20°C freezer. Evaporate one 500µl aliquot of the sample in the Labconco Centrivap cold trap concentrator to complete dryness The dried aliquot is then re-suspended with 500?l 50% acetonitrile (degassed as given) Centrifuge for 2 min at 14000 rcf using the centrifuge Eppendorf 5415. Remove supernatant to a new Eppendorff tube. Evaporate the supernatant to dryness in the the Labconco Centrivap cold trap concentrator. Submit to derivatization. The residue should contain membrane lipids because these are supposedly not soluble enough to be found in the 50% acetonitrile solution. Therefore, this ‘membrane residue’ is now taken for membrane lipidomic fingerprinting using the nanomate LTQ ion trap mass spectrometer. Likely, a good solvent to redissolve the membrane lipids is e.g. 75% isopropanol (degassed as given above). If the ‘analysis’ aliquot is to be used for semi lipophilic compounds such as tyrosine pathway intermediates (incl. dopamine, serotonine etc, i.e. polar aromatic compounds), then these are supposedly to be found together with the ‘GCTOF’ aliquot. We can assume that this mixture is still too complex for Agilent chipLCMS. Therefore, in order to develop and validate target analysis for such aromatic compounds, we should use some sort of Solid Phase purification. We re-suspend the dried ‘GCTOF’ aliquot in 300 ?l water (degassed as before) to take out sugars, aliphatic amino acids, hydroxyl acids and similar logP compounds. The residue should contain our target aromatics .We could also try to adjust pH by using low concentration acetate or phosphate buffer. The residue could then be taken up in 50% acetonitrile and used for GCTOF and Agilent chipMS experiments. The other aliquot should be checked how much of our target compounds would actually be found in the ‘sugar’ fraction. 6. Problems To prevent contamination disposable material is used. Control pH from extraction mix. 7. Quality assurance For each sequence of sample extractions, perform one blank negative control extraction by applying the total procedure (i.e. all materials and plastic ware) without biological sample. 8. Disposal of waste Collect all chemicals in appropriate bottles and follow the disposal rules."},

"CHROMATOGRAPHY":{"CHROMATOGRAPHY_SUMMARY":"Primary metabolism by GCTOF","CHROMATOGRAPHY_TYPE":"GC","INSTRUMENT_NAME":"Gerstel CIS4 –with dual MPS Injector/ Agilent 6890 GC- Pegasus III TOF MS","COLUMN_NAME":"Restek Rtx-5Sil MS (30 x 0.25mm, 0.25um)"},

"ANALYSIS":{"ANALYSIS_TYPE":"MS"},

"MS":{"INSTRUMENT_NAME":"Leco Pegasus IV TOF","INSTRUMENT_TYPE":"GC-TOF","MS_TYPE":"EI","ION_MODE":"UNSPECIFIED","MS_COMMENTS":"A Leco Pegasus IV time of flight mass spectrometer is controlled by the Leco ChromaTOF software vs. 2.32 (St. Joseph, MI). The transfer line temperature between gas chromatograph and mass spectrometer is set to 280°C. Electron impact ionization at 70V is employed with an ion source temperature of 250°C. Acquisition rate is 17 spectra/second, with a scan mass range of 85-500 Da."},

"MS_METABOLITE_DATA":{
"Units":"normalized peak height",

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