Summary of Study ST001788

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 PR001029. The data can be accessed directly via it's Project DOI: 10.21228/M8PM56 This work is supported by NIH grant, U2C- DK119886.

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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 IDST001788
Study Titleβ-Adrenergic regulation of metabolism in macrophages (part-IV)
Study SummaryMacrophages have important roles in the immune system including clearing pathogens and wound healing. Metabolic phenotypes have been associated with functional phenotypes, where pro-inflammatory macrophages have an increased rate of glycolysis and anti-inflammatory macrophages primarily use oxidative phosphorylation. β-adrenoceptor (βAR) signalling in macrophages has been implicated in disease states such as cancer, atherosclerosis and rheumatoid arthritis. The impact of β-adrenoceptor signalling on macrophage metabolism has not been defined. Here we expand on defining the phenotype of macrophages treated with isoprenaline and describe the impact that βAR signalling has on the metabolome and proteome. We found that βAR signalling alters proteins involved in cytoskeletal rearrangement and redox control of the cell. We showed that βAR signalling in macrophages shifts glucose metabolism from glycolysis towards the tricarboxylic acid cycle and pentose phosphate pathways. We also show that βAR signalling perturbs purine metabolism by accumulating adenylate pools. Taken together these results indicate that βAR signalling shifts metabolism to support redox perturbations and upregulate proteins involved in cytoskeletal changes that may impact migration and phagocytosis processes.
Institute
Monash University
Last NamePeterson
First NameAmanda
AddressDrug delivery, disposition and dynamics, Pharmacy and Pharmaceutical Sciences, 381 Royal Parade, Parkville, Victoria, 3052, Australia
Emailamanda.peterson@monash.edu
Phone99039282
Submit Date2021-05-13
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2021-05-28
Release Version1
Amanda Peterson Amanda Peterson
https://dx.doi.org/10.21228/M8PM56
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Combined analysis:

Analysis ID AN002899 AN002900
Analysis type MS MS
Chromatography type HILIC HILIC
Chromatography system Thermo Dionex Ultimate 3000 Thermo Dionex Ultimate 3000
Column ZIC-pHILIC (150 x 4.6mm,5um) ZIC-pHILIC (150 x 4.6mm,5um)
MS Type ESI ESI
MS instrument type Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap
Ion Mode POSITIVE NEGATIVE
Units Intensity Intensity

MS:

MS ID:MS002691
Analysis ID:AN002899
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Mass spectrometry was performed in polarity switching mode, with the following settings: resolution 35 000, AGC 1x106, m/z range 85-1275, sheath gas 50, auxiliary gas 20, sweep gas 2, probe temperature 150 °C, and capillary temperature 300 °C. For positive ionisation mode the source voltage was set at +4 kV and the S-lens voltage at +50 V. For negative ionisation mode the source voltage was set at -3.5 kV and the S-lens voltage at -50 V. Mass calibration was performed for each polarity before running a metabolomics batch to ensure mass accuracy of < 2 ppm. Approximately 300 authentic metabolite standards were analysed at the start of each batch to provide accurate retention times to facilitate metabolite identification. Metabolomics samples were analysed in random order with periodic injections of the pooled QC, and blank samples, to assess analytical quality and aid downstream metabolite identification procedures. Metabolomics LC-MS Data Processing Raw metabolite data was processed using XCMS (Centwave) software for peak picking and mzMatch.R software for alignment and annotation of related metabolite peaks. Metabolites were then identified using the Excel-based IDEOM software by matching the mass of each peak and its retention time with a database, using a mass accuracy window of 2 ppm and a retention time window of 5% for metabolites matching authentic standards, and 35% for other putative metabolites based on a retention time prediction model (15). Noise and mass spectrometry artefacts were filtered using previously described algorithms (15, 16) to minimise false identifications. Detection of stable isotope labelled metabolite peaks were performed using mzMatch-ISO (17). Initial statistical analysis was performed with IDEOM using peak intensities (height) for all detected putative metabolites. Untargeted multivariate analysis was performed using MetaboAnalyst 4.0 (18), where the complete data sets were also analysed using enrichment analysis and pathway analysis functions (19, 20). Further analysis was undertaken using TraceFinderTM (Thermo) to obtain manually curated accurate peak areas for targeted univariate analyses for metabolites in key pathways. Metabolomics data are presented as fold-change values from 2 individual experiments, each with 4 replicates. Labelled metabolomics data is from a single metabolomics experiment and presented as a mean ± SD. Differences were determined using Student’s t-test where significant interactions were observed. Significance was determined at p values < 0.05.
Ion Mode:POSITIVE
  
MS ID:MS002692
Analysis ID:AN002900
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Mass spectrometry was performed in polarity switching mode, with the following settings: resolution 35 000, AGC 1x106, m/z range 85-1275, sheath gas 50, auxiliary gas 20, sweep gas 2, probe temperature 150 °C, and capillary temperature 300 °C. For positive ionisation mode the source voltage was set at +4 kV and the S-lens voltage at +50 V. For negative ionisation mode the source voltage was set at -3.5 kV and the S-lens voltage at -50 V. Mass calibration was performed for each polarity before running a metabolomics batch to ensure mass accuracy of < 2 ppm. Approximately 300 authentic metabolite standards were analysed at the start of each batch to provide accurate retention times to facilitate metabolite identification. Metabolomics samples were analysed in random order with periodic injections of the pooled QC, and blank samples, to assess analytical quality and aid downstream metabolite identification procedures. Metabolomics LC-MS Data Processing Raw metabolite data was processed using XCMS (Centwave) software for peak picking and mzMatch.R software for alignment and annotation of related metabolite peaks. Metabolites were then identified using the Excel-based IDEOM software by matching the mass of each peak and its retention time with a database, using a mass accuracy window of 2 ppm and a retention time window of 5% for metabolites matching authentic standards, and 35% for other putative metabolites based on a retention time prediction model (15). Noise and mass spectrometry artefacts were filtered using previously described algorithms (15, 16) to minimise false identifications. Detection of stable isotope labelled metabolite peaks were performed using mzMatch-ISO (17). Initial statistical analysis was performed with IDEOM using peak intensities (height) for all detected putative metabolites. Untargeted multivariate analysis was performed using MetaboAnalyst 4.0 (18), where the complete data sets were also analysed using enrichment analysis and pathway analysis functions (19, 20). Further analysis was undertaken using TraceFinderTM (Thermo) to obtain manually curated accurate peak areas for targeted univariate analyses for metabolites in key pathways. Metabolomics data are presented as fold-change values from 2 individual experiments, each with 4 replicates. Labelled metabolomics data is from a single metabolomics experiment and presented as a mean ± SD. Differences were determined using Student’s t-test where significant interactions were observed. Significance was determined at p values < 0.05.
Ion Mode:NEGATIVE
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