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Masshunter quant

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MassHunter Quant is a software solution for quantitative analysis of mass spectrometry data. It provides tools for processing, visualizing, and reporting results from sample analysis.

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Lab products found in correlation

Masshunter software, by Agilent Technologies (2 mentions) Tracefinder software version 4, by Thermo Fisher Scientific (1 mentions) Succinic acid d4, by Merck Group (1 mentions) 7200 gc qtof, by Agilent Technologies (1 mentions)

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MassHunter Quant software (6 citations)

6 protocols using masshunter quant

1

Quantitative Metabolomics Analysis of Cellular Response

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All data except the untargeted metabolomics analysis were quantified by integrating the area under the curve of each metabolite and its isotopologue using MassHunter Quant (Agilent Technologies). Each metabolite’s accurate mass ion and subsequent isotopic ions were extracted (EIC) using a 10 ppm window. In the case of isotopic labeling with 13C6-glucose or 15N2-arginine, corrections for natural enrichments were generated for each metabolite (Ctotal−1 or Ntotal−1) using a previously developed algorithm42 (link). MIDs of the indicated metabolites were calculated as previously described42 (link) and expressed as percent of the untreated PBS control set at 1.0. Pathway enrichment, principal component analysis (PCA), fold change and ANOVA statistical analysis were performed using Metaboanalyst software (www.metaboanalyst.ca). Pathway analysis was performed comparing the log2 fold change data between two conditions per analysis, BAD SAHBA SD versus vehicle, and BAD SAHBA SD versus RO0281675, all in the presence of cytokines (Fig. 1i).
Fu A., Alvarez-Perez J.C., Avizonis D., Kin T., Ficarro S.B., Choi D.W., Karakose E., Badur M.G., Evans L., Rosselot C., Bridon G., Bird G.H., Seo H.S., Dhe-Paganon S., Kamphorst J.J., Stewart A.F., Shapiro A.M., Marto J.A., Walensky L.D., Jones R.G., Garcia-Ocana A, & Danial N.N. (2020). Glucose-dependent partitioning of arginine to the urea cycle protects β-cells from inflammation. Nature metabolism, 2(5), 432-446.
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2

Metabolomic Analysis of BAD SAHB vs Vehicle

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All data except the untargeted metabolomics analysis were quantified by integrating the area under the curve of each metabolite using MassHunter Quant (Agilent Technologies). Pathway enrichment analyses were performed using Metaboanalyst software (https://www.metaboanalyst.ca/) based on KEGG metabolic pathways. Pathway analysis was performed comparing the relative metabolite levels between BAD SAHBA SD and vehicle, in the presence of cytokines (Figure S1A). The impact score represents the number of nodes contained in the data and the adjusted p value was obtained using Holm adjustments (Xia and Wishart, 2011 (link)). Targeted processing of GSH and isotopolog for data collected using LCMS “method D” was conducted using TraceFinder software version 4.1 (Thermo Fisher Scientific). Compound identities were confirmed using reference standards. GSH metabolite isotopolog abundances were normalized to the recovery of internal standards inosine-15N4, thymine-D4 and glycocholate-D4. Total ion counts of each mass isotopolog of GSH were corrected for natural abundances of 13C and fractional labeling out of the total pools of GSH were calculated in Excel.
Fu A., van Rooyen L., Evans L., Armstrong N., Avizonis D., Kin T., Bird G.H., Reddy A., Chouchani E.T., Liesa-Roig M., Walensky L.D., James Shapiro A.M, & Danial N.N. (2021). Glucose metabolism and pyruvate carboxylase enhance glutathione synthesis and restrict oxidative stress in pancreatic islets. Cell reports, 37(8), 110037.
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3

Targeted Metabolite Identification and Quantification

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Metabolite identification was confirmed by exact mass, retention time and subsequent MS/MS fragmentation of metabolite standards and quality control samples. These identifications correspond to Metabolomics Standards Initiative identification level 1 (Sumner et al., 2007 (link)). A targeted list of metabolites was quantified (relative quantification) by external standard calibration curves with Mass Hunter Quant (Agilent).
Menzies C., Naz S., Patten D., Alquier T., Bennett B.M, & Lacoste B. (2021). Distinct Basal Metabolism in Three Mouse Models of Neurodevelopmental Disorders. eNeuro, 8(2), ENEURO.0292-20.2021.
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4

Quantitative Metabolomics Analysis of Cellular Response

Cited 1 time
Check if the same lab product or an alternative is used in the 5 most similar protocols
All data except the untargeted metabolomics analysis were quantified by integrating the area under the curve of each metabolite and its isotopologue using MassHunter Quant (Agilent Technologies). Each metabolite’s accurate mass ion and subsequent isotopic ions were extracted (EIC) using a 10 ppm window. In the case of isotopic labeling with 13C6-glucose or 15N2-arginine, corrections for natural enrichments were generated for each metabolite (Ctotal−1 or Ntotal−1) using a previously developed algorithm42 (link). MIDs of the indicated metabolites were calculated as previously described42 (link) and expressed as percent of the untreated PBS control set at 1.0. Pathway enrichment, principal component analysis (PCA), fold change and ANOVA statistical analysis were performed using Metaboanalyst software (www.metaboanalyst.ca). Pathway analysis was performed comparing the log2 fold change data between two conditions per analysis, BAD SAHBA SD versus vehicle, and BAD SAHBA SD versus RO0281675, all in the presence of cytokines (Fig. 1i).
Fu A., Alvarez-Perez J.C., Avizonis D., Kin T., Ficarro S.B., Choi D.W., Karakose E., Badur M.G., Evans L., Rosselot C., Bridon G., Bird G.H., Seo H.S., Dhe-Paganon S., Kamphorst J.J., Stewart A.F., Shapiro A.M., Marto J.A., Walensky L.D., Jones R.G., Garcia-Ocana A, & Danial N.N. (2020). Glucose-dependent partitioning of arginine to the urea cycle protects β-cells from inflammation. Nature metabolism, 2(5), 432-446.
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5

GC-MS Analysis of Liver Tumor Metabolites

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Approximately 50 mg of snap-frozen mouse liver tumors was determined by GC-MS analysis as previously reported (19 (link)). Metabolites were extracted with cold 90% methanol and an internal standard d4-succinic acid (Sigma) was added for every 25 mg of tissue. The samples were homogenized, and supernatant was collected by centrifugation and another internal standard, d27-myristic acid, was added. All samples were then dried en vacuo and resuspended in pyridine containing 40 mg/ml O-methoxylamine hydrochloride (MOX) before GC-MS analysis on an Agilent Zorbax DB-5MS column. Metabolites were identified and their peak area was recorded using MassHunter Quant and analyzed with MassHunter software (Agilent). Statistical analysis was performed using MetaboAnalystR.
Guzzo J, & Dubow M.S. (2000). A Novel Selenite- and Tellurite-Inducible Gene in Escherichia coli. Applied and Environmental Microbiology, 66(11), 4972-4978.
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6

GC-MS Metabolomics Analysis of Cardiac Samples

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The method of metabolomics analysis has been described previously (37 (link)). Briefly, gas chromatography/mass spectrometry–based (GC/MS-based) metabolomics analysis was performed using ventricular tissue samples (~15 mg) harvested from control and YAPch-KO mice 2 days after sham operation or TAC or using NRVMs (1 × 107 cells/10 cm dish) transduced with Ad-LacZ or Ad-FLAG-YAP for 5 days. All GC/MS analyses were performed with an Agilent 7200 GC-QTOF and an Agilent 7693A automatic liquid sampler. Data were collected using MassHunter software (Agilent Technologies). Metabolites were identified and their peak areas were recorded using Agilent’s MassHunter Quant. Metabolite identity was established using a combination of an in-house metabolite library developed using pure purchased standards, the National Institute of Standards and Technology (NIST) library, and the Fiehn library. The values were normalized to wet tissue weight. Analysis of the metabolomics data was carried out using MetaboAnalyst 5.0 software, including the generation of a heatmap.
Kashihara T., Mukai R., Oka S.I., Zhai P., Nakada Y., Yang Z., Mizushima W., Nakahara T., Warren J.S., Abdellatif M, & Sadoshima J. (2022). YAP mediates compensatory cardiac hypertrophy through aerobic glycolysis in response to pressure overload. The Journal of Clinical Investigation, 132(6), e150595.
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