{
"METABOLOMICS WORKBENCH":{"STUDY_ID":"ST002240","ANALYSIS_ID":"AN003657","VERSION":"1","CREATED_ON":"July 21, 2022, 10:57 am"},

"PROJECT":{"PROJECT_TITLE":"Using stable isotopes and mass spectrometry to elucidate the dynamics of metabolic pathways","PROJECT_TYPE":"Stable Isotope Enriched Lipidomics","PROJECT_SUMMARY":"Data analysis and mass spectrometry tools have advanced significantly in the last decade. This ongoing revolution has elevated the status of analytical chemistry within the big-data omics era. High resolution mass spectrometers (HRMS) can now distinguish different metabolites with mass to charge ratios (i.e. m/z) that differ by 0.01 Da or less. This unprecedented level of resolution not only enables identification of previously unknown compounds but also presents an opportunity to establish active metabolic pathways through quantification of isotope enrichment. Studies with stable isotope tracers continue to contribute to our knowledge of biological pathways in human, plant and bacterial species, however most current studies have been based on targeted analyses. The capacity of HRMS to resolve near-overlapping isotopologues and identify compounds with high mass precision presents a strategy to assess ‘active’ pathways de novo from data generated in an untargeted way, that is blind to the metabolic network and therefore unbiased. Currently, identifying metabolic features, enriched with stable isotopes, at an ‘omics’ level remains an experimental bottleneck, limiting our capacity to understand biological network operation at the metabolic level. We developed data analysis tools that: i) use labeling information and exact mass to determine the elemental composition of each isotopically enriched ion, ii) apply correlation-based approaches to cluster metabolite peaks with similar patterns of isotopic labels and, iii) leverage this information to build directed metabolic networks de novo. Using Camelina sativa, an emerging oilseed model, we demonstrate the power of stable isotope labeling in combination with imaging and HRMS to reconstruct lipid metabolic networks in developing seeds and are currently addressing questions about lipid and central metabolism. Tools developed in this study will have a broader application to assess context specific operation of metabolic pathways.","INSTITUTE":"Donald Danforth Plant Science Center","DEPARTMENT":"Allen/USDA lab","LABORATORY":"Allen lab","LAST_NAME":"Shrikaar","FIRST_NAME":"Kambhampati","ADDRESS":"975 North Warson road","EMAIL":"skambhampati@danforthcenter.org","PHONE":"3144025550","FUNDING_SOURCE":"NIH, USDA-ARS"},

"STUDY":{"STUDY_TITLE":"Use of HRMS and Dual Isotope Labels to Resolve Difficult-to Measure Fluxes","STUDY_TYPE":"Stable isotope enriched Metabolomics","STUDY_SUMMARY":"Data analysis and mass spectrometry tools have advanced significantly in the last decade. This ongoing revolution has elevated the status of analytical chemistry within the big-data omics era. High resolution mass spectrometers (HRMS) can now distinguish different metabolites with mass to charge ratios (i.e. m/z) that differ by 0.01 Da or less. This unprecedented level of resolution not only enables identification of previously unknown compounds but also presents an opportunity to establish active metabolic pathways through quantification of isotope enrichment. Studies with stable isotope tracers continue to contribute to our knowledge of biological pathways in human, plant and bacterial species, however most current studies have been based on targeted analyses. The capacity of HRMS to resolve near-overlapping isotopologues and identify compounds with high mass precision presents a strategy to assess ‘active’ pathways de novo from data generated in an untargeted way, that is blind to the metabolic network and therefore unbiased. Currently, identifying metabolic features, enriched with stable isotopes, at an ‘omics’ level remains an experimental bottleneck, limiting our capacity to understand biological network operation at the metabolic level. We developed data analysis tools that: i) use labeling information and exact mass to determine the elemental composition of each isotopically enriched ion, ii) apply correlation-based approaches to cluster metabolite peaks with similar patterns of isotopic labels and, iii) leverage this information to build directed metabolic networks de novo. Using Camelina sativa, an emerging oilseed model, we demonstrate the power of stable isotope labeling in combination with imaging and HRMS to reconstruct lipid metabolic networks in developing seeds and are currently addressing questions about lipid and central metabolism. Tools developed in this study will have a broader application to assess context specific operation of metabolic pathways.","INSTITUTE":"Donald Danforth Plant Science Center","DEPARTMENT":"Allen/USDA lab","LABORATORY":"Allen Lab","LAST_NAME":"Shrikaar","FIRST_NAME":"Kambhampati","ADDRESS":"975 North Warson road","EMAIL":"skambhampati@danforthcenter.org","PHONE":"3144025550"},

"SUBJECT":{"SUBJECT_TYPE":"Plant","SUBJECT_SPECIES":"Arabidopsis thaliana","TAXONOMY_ID":"3702","AGE_OR_AGE_RANGE":"10 day old seedlings","SPECIES_GROUP":"Roots"},
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{
"Subject ID":"-",
"Sample ID":"8_WT_4-pos",
"Factors":{"Tissue type":"Wildtype (Col 0)","Time (hours)":"8"},
"Additional sample data":{"Chromatography":"HILIC","Polarity":"Positive","RAW_FILE_NAME":"8_WT_4-pos"}
},
{
"Subject ID":"-",
"Sample ID":"8_WT_4-neg",
"Factors":{"Tissue type":"Wildtype (Col 0)","Time (hours)":"8"},
"Additional sample data":{"Chromatography":"HILIC","Polarity":"Negative","RAW_FILE_NAME":"8_WT_4-neg"}
}
],
"COLLECTION":{"COLLECTION_SUMMARY":"For the metabolomics study using dual-isotope labeling, wildtype Arabidopsis ecotype Columbia seeds were grown on vertical plates at 22°C under continuous light (ca. 70 µmol m-2 s-1), on a defined nutrient medium previously described11. The medium consisted of 10 mM potassium phosphate (pH 6.5), 5 mM KNO3, 2 mM MgSO4, 1 mM CaCl2, 0.1 mM FeNaEDTA, micronutrients (50 mM H3BO3, 12 mM MnSO4, 1 mM ZnCl2, 1 mM CuSO4 and 0.2 mM Na2MoO4), 1% sucrose and 1% agar. Ten-day old seedlings were transferred to plates containing the same medium, except the nitrogen source was replaced with 10 mM [13C5,15N2]glutamine. Root tissue was excised after exposure to medium containing labeled glutamine for 2, 4, 6 and 8h to represent time course incorporation of carbon and nitrogen into metabolism. Untreated roots were used as unlabeled (0h) controls. Each plate yielded ~100 mg of root tissue and served as a single replicate. Four replicates per sample type were collected and flash frozen using liquid N2 for total metabolite extraction.","SAMPLE_TYPE":"Plant","COLLECTION_METHOD":"Flash frozen in Liquid N2","COLLECTION_LOCATION":"Donald Danforth Plant Science Center","STORAGE_CONDITIONS":"-80℃"},

"TREATMENT":{"TREATMENT_SUMMARY":"For the metabolomics study using dual-isotope labeling, wildtype Arabidopsis ecotype Columbia seeds were grown on vertical plates at 22°C under continuous light (ca. 70 µmol m-2 s-1), on a defined nutrient medium previously described11. The medium consisted of 10 mM potassium phosphate (pH 6.5), 5 mM KNO3, 2 mM MgSO4, 1 mM CaCl2, 0.1 mM FeNaEDTA, micronutrients (50 mM H3BO3, 12 mM MnSO4, 1 mM ZnCl2, 1 mM CuSO4 and 0.2 mM Na2MoO4), 1% sucrose and 1% agar. Ten-day old seedlings were transferred to plates containing the same medium, except the nitrogen source was replaced with 10 mM [13C5,15N2]glutamine. Root tissue was excised after exposure to medium containing labeled glutamine for 2, 4, 6 and 8h to represent time course incorporation of carbon and nitrogen into metabolism. Untreated roots were used as unlabeled (0h) controls. Each plate yielded ~100 mg of root tissue and served as a single replicate. Four replicates per sample type were collected and flash frozen using liquid N2 for total metabolite extraction."},

"SAMPLEPREP":{"SAMPLEPREP_SUMMARY":"Frozen Arabidopsis root tissue was homogenized using a tissue lyser, and extraction was carried out using 1 mL of 4:1 methanol: water (v/v) with incubation in an ultra-sonication bath for 30 min followed by shaking for 30 min at 4°C. The mixture was then centrifuged at 21,000 x g for 10 min at 4°C; supernatant was transferred into fresh tubes and evaporated to dryness using a speedvac centrifuge at ambient temperature. Dried residue was re-suspended in 200 µL of 1:1 methanol: water (v/v), filtered using 0.2 µm PTFE micro centrifuge filters and transferred to glass vials for HILIC-HRMS runs.","PROCESSING_STORAGE_CONDITIONS":"-80℃","EXTRACTION_METHOD":"4:1 Methanol:Water"},

"CHROMATOGRAPHY":{"CHROMATOGRAPHY_SUMMARY":"Chromatographic separation using HILIC was achieved using an Agilent 1290 Infinity II UHPLC system equipped with a SeQuant® ZIC®-HILIC (100 x 2.1 x 3.5 µm) column (EMD Millipore, Burlington, MA). Mobile phases A and B were comprised of 5 mM ammonium acetate (pH 4.0) in water and 90% acetonitrile with 0.1 % acetic acid, respectively. A flow rate of 0.3 mL min-1 was used to elute compounds with the following gradient: 87% B for 5 minutes, decreased to 55% B over the next 8 minutes and held for 2.5 minutes before returning to 87% and equilibrating the column for 3 minutes.","CHROMATOGRAPHY_TYPE":"HILIC","INSTRUMENT_NAME":"Agilent 1290 Infinity II","COLUMN_NAME":"SeQuant ZIC-HILIC (100 x 2.1mm, 3.5um)","FLOW_RATE":"0.3 mL min-1","COLUMN_TEMPERATURE":"40","SOLVENT_A":"5 mM ammonium acetate (pH 4.0) in water","SOLVENT_B":"90% acetonitrile with 0.1 % acetic acid","INTERNAL_STANDARD":"Equisplash"},

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

"MS":{"INSTRUMENT_NAME":"Thermo Q Exactive Orbitrap","INSTRUMENT_TYPE":"Orbitrap","MS_TYPE":"ESI","ION_MODE":"POSITIVE","MS_COMMENTS":"The heated electrospray ionization (HESI) conditions used were as follows; spray voltage, 3.9 kV (ESI+), 3.5 kV (ESI-); capillary temperature, 250 °C; probe heater temperature, 450 °C; sheath gas, 30 arbitrary units; auxiliary gas, 8 arbitrary units; and S-Lens RF level, 60%. Full MS data were collected using a Q-Exactive Quadrupole Orbitrap mass spectrometer (Thermo Fisher Scientific) in both positive and negative ionization mode separately from mass ranges 75-1100 m/z and 65-900 m/z, respectively, at 140,000 resolution. The automatic gain control (AGC) was set to 3 x 106 and maximum injection time (IT) used was 524 ms.","MS_RESULTS_FILE":"ST002240_AN003657_Results.txt UNITS:Intensity Has m/z:Yes Has RT:Yes RT units:Minutes"}

}