{
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"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, St. Louis, MO 63132","EMAIL":"skambhampati@danforthcenter.org","PHONE":"3144025550","FUNDING_SOURCE":"NIH, USDA-ARS","DOI":"http://dx.doi.org/10.21228/M80X3B"},

"STUDY":{"STUDY_TITLE":"Insights into plant lipid metabolism using stable isotopes and high resolution mass spectrometry","STUDY_TYPE":"Stable isotope enriched lipidomics","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","SUBMIT_DATE":"2022-07-21"},

"SUBJECT":{"SUBJECT_TYPE":"Plant","SUBJECT_SPECIES":"Camelina Sativa","AGE_OR_AGE_RANGE":"10 days after fertilization","SPECIES_GROUP":"Developing seeds"},
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],
"COLLECTION":{"COLLECTION_SUMMARY":"Plant growth and culture conditions: Plants were grown in greenhouses with day/night temperature maintained at 22/20°C, 40-50% relative humidity, and 16h day/8h night photoperiod. Intact siliques during the seed filling growth stage (15 days after fertilization) were excised and placed in sterile media containing a modified Linsmaier and Skoog medium23,24 with Gamborg’s vitamins (Sigma) and 5 mM MES buffer adjusted to pH 5.8. Fifty mM [U-13C6]glucose was used as labeled substrate, and the composition of the remaining carbon and nitrogen sources represented maternal phloem composition to minimize metabolic perturbation and to maintain pseudo in vivo conditions as previously described25. Silique culturing was performed in a 96-well plate with 0.3 mL of medium and a single silique per well, under continuous light (250 µmol m-2 s-1). Tissue was collected and flash frozen immediately after each time point (2, 4, 8, 16 and 32h). Uncultured siliques excised from the maternal plant were used as unlabeled (0h) controls. Frozen tissue was sectioned, on top of dry ice, to excise embryo from the siliques and to separate cotyledons from the embryo axis. Cotyledon samples were extracted and analyzed for lipids in triplicates.","COLLECTION_PROTOCOL_FILENAME":"13CLipids_CamelinaSeeds_Methods.docx","SAMPLE_TYPE":"Seeds","COLLECTION_LOCATION":"Donald Danforth Plant Science Center","STORAGE_CONDITIONS":"-80℃"},

"TREATMENT":{"TREATMENT_SUMMARY":"Plants were grown in greenhouses with day/night temperature maintained at 22/20°C, 40-50% relative humidity, and 16h day/8h night photoperiod. Intact siliques during the seed filling growth stage (15 days after fertilization) were excised and placed in sterile media containing a modified Linsmaier and Skoog medium23,24 with Gamborg’s vitamins (Sigma) and 5 mM MES buffer adjusted to pH 5.8. Fifty mM [U-13C6]glucose was used as labeled substrate, and the composition of the remaining carbon and nitrogen sources represented maternal phloem composition to minimize metabolic perturbation and to maintain pseudo in vivo conditions as previously described25. Silique culturing was performed in a 96-well plate with 0.3 mL of medium and a single silique per well, under continuous light (250 µmol m-2 s-1). Tissue was collected and flash frozen immediately after each time point (2, 4, 8, 16 and 32h). Uncultured siliques excised from the maternal plant were used as unlabeled (0h) controls. Frozen tissue was sectioned, on top of dry ice, to excise embryo from the siliques and to separate cotyledons from the embryo axis. Cotyledon samples were extracted and analyzed for lipids in triplicates."},

"SAMPLEPREP":{"SAMPLEPREP_SUMMARY":"Frozen cotyledon samples from Camelina were homogenized using a tissue lyser and the extraction of lipids was carried out using a phase separation method previously described26. Briefly, 1 mL 7:3 methanol:chloroform (-20°C) containing the ultimateSPLASHTM ONE lipid mix (Avanti Polar lipids, Alabaster, AL) as internal standard (1:20 dilution) was added to the samples, vortexed vigorously and incubated on a rotary shaker for 2 hours at 4°C. After incubation, 500 µL of ice-cold water was added to the samples, vortexed and centrifuged at 14,000 rpm at 4°C for 10 min to achieve phase separation. The upper aqueous phase was carefully removed, 200 µL of methanol was added to the remaining organic phase containing lipids and centrifuged at 14,000 rpm for 5 min to pellet the debris. The organic phase (supernatant) was transferred to a glass tube and dried using a speedvac centrifuge. Samples were re-suspended in 200 µL of 49:49:2 acetonitrile: methanol: chloroform, filtered using 0.2 µm PTFE microcentrifuge filters and transferred to a glass vial for RPLC-HRMS analysis.","PROCESSING_STORAGE_CONDITIONS":"-80℃","EXTRACTION_METHOD":"methanol:chloroform:water"},

"CHROMATOGRAPHY":{"CHROMATOGRAPHY_SUMMARY":"Separations for lipidomics were achieved using the loading pump of a Dionex UltiMate 3000 RSLCnano system (Thermo Fisher Scientific) operating at a flow rate of 40 µL min-1 equipped with a custom-made C8 column (100 x 0.5 x 5 µm) from Higgins Analytical Inc. (Mountain view, CA) re-packed from a nucleodur C8 Gravity column (Macherey-Nagel, Allentown, PA). Mobile phases comprised of 1% 1 M ammonium acetate, 0.1 % acetic acid in water (A) and 1% 1 M ammonium acetate, 0.1% acetic acid in 7:3 (v/v) acetonitrile: isopropanol (B). The following gradient modified from a previously described method27 to adapt to micro flow was used; 0-1 min at 55% B, 4 min at 75% B, 12 min at 89% B, 15 min at 99% B, 18 min at 99% B and 20 min at 55% B followed by equilibration up to 30 min.","INSTRUMENT_NAME":"Dionex UltiMate 3000 RSLCnano","COLUMN_NAME":"Custom C8 - Higgins Analytical","COLUMN_TEMPERATURE":"40","FLOW_RATE":"0.04 mL min-1","INTERNAL_STANDARD":"Equisplash","SOLVENT_A":"1% 1 M ammonium acetate, 0.1 % acetic acid in water","SOLVENT_B":"1% 1 M ammonium acetate, 0.1% acetic acid in 7:3 (v/v) acetonitrile: isopropanol","CHROMATOGRAPHY_TYPE":"Reversed phase"},

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

"MS":{"INSTRUMENT_NAME":"Thermo Fusion Tribrid Orbitrap","INSTRUMENT_TYPE":"Orbitrap","MS_TYPE":"ESI","MS_COMMENTS":"The eluent was sprayed on to the HESI source of an Orbitrap Fusion Lumos Tribrid MS, operated with sheath gas, 25 arbitrary units; auxiliary gas, 5 arbitrary units; ion transfer tube temperature, 300oC; vaporizer temperature, 100oC; and S-lens RF level, 60. The spray voltage was 4 kV in both positive and negative modes. Full MS data were collected for mass ranges 450-1200 m/z at 240,000 resolution from both positive and negative modes simultaneously, using polarity switch. The AGC target was set to “Standard” and the maximum IT was set to 100 ms.","ION_MODE":"NEGATIVE","MS_RESULTS_FILE":"ST002239_AN003656_Results.txt UNITS:Intensity Has m/z:Yes Has RT:Yes RT units:Minutes"}

}