Masshunter qqq quantitative analysis software

Manufactured by Agilent Technologies

Sourced in Australia

MassHunter QQQ Quantitative Analysis software is a data analysis tool designed for use with Agilent's triple quadrupole mass spectrometers. The software provides functionality for processing and quantifying data from these instruments.

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Lab products found in correlation

Xbridge amide column, by Waters Corporation (2 mentions) 1290 series hplc system, by Agilent Technologies (1 mentions) Zorbax eclipse plus c18 column, by Agilent Technologies (1 mentions) 6490 triple quadrupole mass spectrometer, by Agilent Technologies (1 mentions) 6430 triple quadrupole lc ms system, by Agilent Technologies (1 mentions)

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MassHunter software (440 citations) MassHunter Quantitative Analysis software (110 citations) MassHunter Quantitative Analysis (38 citations) Quantitative Analysis software (17 citations) MassHunter Workstation QqQ Quantitative Analysis Software (5 citations) QQQ Quantitative Analysis software (2 citations)

8 protocols using masshunter qqq quantitative analysis software

Quantification of Lipid Molecular Species

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Relative quantification data were extracted using Agilent MassHunter Quantitative Analysis (QQQ) software. The data were manually curated to ensure that the software integrated the right peaks. Areas under curve (AUC) of the extracted ion chromatograms peaks for each SIM/MRM transition were extracted to Excel. A correction factor was applied to account for the multiplicity of fatty acids in some molecular species of TAG (e.g. TAG 18:1 18:1 18:1). For HILIC, isotopic correction was performed on AUC of the phospholipids according to [52] (link). AUCs were normalised either to that of internal standards and to sample weight, or to total intensity in a lipid class. Statistical analysis was performed using a generalised linear model with gaussian distribution.

Woodfield H.K., Cazenave-Gassiot A., Haslam R.P., Guschina I.A., Wenk M.R, & Harwood J.L. (2018). Using lipidomics to reveal details of lipid accumulation in developing seeds from oilseed rape (Brassica napus L.). Biochimica et Biophysica Acta, 1863(3), 339-348.

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Targeted Lipid Profiling by LC-MS/MS

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Analyses of plasma lipids was performed on the Agilent 6490 LC-QQQ mass spectrometer interfaced with an Agilent 1290 series HPLC system. Separation of lipids were conducted on a ZORBAX eclipse plus C18 column (2.1 × 100 mm 1.8 mm, Agilent technologies) with the temperature of 60 °C with solvent A and B made up of water, acetonitrile, and isopropanol (50:30:20 and 1:9:90 respectively) with 10 mM ammonium formate.
Targeted mass spectrometry analysis was conducted in ESI positive ion mode with dynamic scheduled multiple reaction monitoring. Mass spectrometry settings and multiple reaction monitoring transitions for each lipid subclass and individual species was run as previously described.¹⁶ (link)^,¹⁷ (link)
Mass spectrometer running conditions were as follows: gas temperature 150 °C, gas flow rate 17 l/min, nebulizer gas pressure 20 psi, sheath gas temperature 200 °C, capillary voltage 3500 V and sheath gas flow 10 l/min. Isolation widths for Q1 and Q3 were set to unit resolution (0.7 amu) for both Q1 and Q3. QC samples were analysed with batch samples to monitor sample extraction efficiency. Data processing of each lipid species was performed using Agilent's Mass Hunter Quantitative Analysis (QQQ) software (Agilent Technologies Australia) to determine the area of the resultant chromatograms for the lipid species.

Bartho L.A., Keenan E., Walker S.P., MacDonald T.M., Nijagal B., Tong S, & Kaitu'u-Lino T.J. (2023). Plasma lipids are dysregulated preceding diagnosis of preeclampsia or delivery of a growth restricted infant. eBioMedicine, 94, 104704.

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Plasma Metabolite Profiling Using LCMS

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Polar metabolites were extracted using protein precipitation from 30 μL of EDTA plasma. The extracted metabolites from the supernatant were separated on Xbridge Amide columns (2.1×100 mm 3.5 μm, Waters) using our previously described methods [28 ,29 (link)]. With this method, 139 transitions were monitored (Supplementary Table 1). Peak integration for metabolite quantification was carried out using MassHunter QQQ Quantitative Analysis software (Agilent).

Ament Z., Bevers M.B., Wolcott Z., Kimberly W.T, & Acharjee A. (2020). Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke. Translational stroke research, 12(2), 293-302.

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Targeted Lipidomic Analysis of Plasma

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Lipid metabolites were extracted from 50 μL of plasma by liquid-liquid extraction.
Samples were analyzed using an ACE C18-PFP, 3μm, Ultra-Inert HPLC Column, 150 x 2.1mm for the detection of free fatty acids and endocannabinoids in negative and positive ionization, respectively. This part of the analysis quantified 16 metabolites (Supplementary Table 1.)
For open profiling lipidomic analysis, 1 μL of each sample was injected and analyzed. Chromatographic separation was performed with a Kinetex C18 (2.1 mm× 100 mm, 2.6 μm) [30 (link)]. MassHunter QQQ Quantitative Analysis software (Agilent) was used for peak integration of 135 transitions (Supplementary Table 1.)

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Targeted Plasma Metabolomics Analysis

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A targeted metabolomics approach was selected to measure a predefined panel of metabolites, as previously described^{27 (link)–30 (link)}. Briefly, polar metabolites were extracted using protein precipitation from 30 μL of EDTA plasma. Sample extraction was carried out over ice. Isotopic standards were included for quality control monitoring, including proline (¹³C₅, ¹⁵N), glutamine (¹³C₅, ¹⁵N₂), deuterated leucine-d10, and phenylalanine-d8. Isotopic standards were obtained from Cambridge Isotope Laboratories (Tewksbury, MA). The extracted metabolites from the supernatant were separated on Xbridge Amide columns (2.1×100 mm 3.5 μm, Waters, Milford, MA), applying previously described methods using dual Infinity II 1290 HLPC pumps and a 6495 QQQ tandem mass spectrometer (Agilent, Santa Clara, CA). The QQQ mass spectrometer design was optimized to quantify 162 plasma metabolites involved in well-known, biologically important pathways. Human pooled plasma samples were also extracted and injected after every 10 samples for quality control assessments. All peaks were integrated and reviewed using MassHunter QQQ Quantitative Analysis software (Agilent). Following peak integration, metabolites were normalized to the nearest pooled plasma samples using standard approaches^{27 (link)–30 (link)}.

Bhave V.M., Ament Z., Patki A., Gao Y., Kijpaisalratana N., Guo B., Chaudhary N.S., Garcia Guarniz A.L., Gerszten R., Correa A., Cushman M., Judd S., Irvin M.R, & Kimberly W.T. (2022). Plasma metabolites link dietary patterns to stroke risk. Annals of neurology, 93(3), 500-510.

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Plasma Metabolomics Profiling Methods

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Methods for metabolomics profiling in human plasma have been described (12 ). In brief, to measure N-oleoyl-leucine/phenylalanine/glycine/and serine, chromatography was performed using an Agilent 1290 infinity LC system equipped with a Waters XBridge Amide column, coupled to an Agilent 6490 triple quadrupole mass spectrometer. To measure endogenous hydroxy-oleoyl-leucine, chromatography was performed using a Waters UPLC BEH Amide (1.7um, 1.0 × 150 mm) column. Metabolite transitions were assayed using a dynamic multiple reaction monitoring systems. LC-MS data were analyzed with Agilent Masshunter QQQ Quantitative analysis software. Isotope-labeled internal standards were monitored in each sample to ensure proper MS sensitivity for quality control. Pooled plasma samples were interspersed at intervals of ten participant samples to enable correction of drift in instrument sensitivity over time and to scale data between batches. A linear scaling approach was used to the nearest pooled plasma sample in the queue.

Tanzo J.T., Li V.L., Wiggenhorn A.L., Moya-Garzon M.D., Wei W., Lyu X., Dong W., Tahir U.A., Chen Z.Z., Cruz D.E., Deng S., Shi X., Zheng S., Guo Y., Sims M., Abu-Remaileh M., Wilson J.G., Gerszten R.E., Long J.Z, & Benson M.D. (2023). CYP4F2 is a human-specific determinant of circulating N-acyl amino acid levels. The Journal of Biological Chemistry, 299(6), 104764.

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LC-MS Quantification of Analytes

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LC-MS was conducted using an Agilent 6430 Triple Quadrupole LC/MS System. The LC solvents were 0.1 %v/v formic acid in H 2 O (A) and 0.1 %v/v formic acid in acetonitrile (B) (both solvents were Honeywell LC-MS Grade LabReady Blends). The flow rate was 200 µL and the gradient was as follows: 0.0 % B from 0.00 to 3.00 min, increasing steadily to 100 % B at 6.00 min; the solvent composition remained at 100 % B until 8.00 min, after which it returned to 0.0 % B over 0.50 min and the system was allowed to equilibrate at this solvent composition for 20 min. The MS was operated in positive ion mode with an ion source temperature of 125 C, capillary voltage of 4.0 kV, a desolvation (N 2 ) gas flow of 11 L/min and a nebulizer pressure of 15 psi. MRM was used to quantify all analytes (Supplemental Table S1). The cell accelerator voltage for each MRM transition was 4 V. Data was analysed using the Agilent MassHunter QQQ Quantitative Analysis software.

Tivendale N.D., Fenske R., Duncan O., & Millar A.H. (2021). In vivo homopropargylglycine incorporation enables nascent protein tagging, isolation and characterisation from Arabidopsis thaliana.

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Quantifying Allantoin via GC-MS

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Allantoin and 13 C 15 N-allantoin standards were purchased from Sigma Aldrich (Australia). Retention time, a corresponding unique precursor ion and product ions were identified on the GC-QqQ-MS instrument for each standard. Collision energy was optimised between 0 and 20 V for the identified precursor to product ion transitions (Multiple Reaction Monitoring; MRM). A product ion was selected as the Target ion (T) and the other subsequent MRM transition was set as the Qualifier ion (Q) (see Table S2 for details). Linearity of the method was tested using serial dilutions of the calibration standard and showed a linear calibration range between 0.98 µM to 250 µM 13 C 15 N-allantoin. Correlation coefficient (R 2 ) of the calibration curve was 0.99 for the target allantoin MRM (398 → 171). The limit of detection for the allantoin MRM, was 0.294 µM based on a signal to noise ratio of 3.
Data was processed using Agilent MassHunter QQQ Quantitative Analysis software (B.07.00). Allantoin was quantified by single point calibration based on the relative response (the response area of allantoin (MRM 398 → 171) divided by the response area of 13 C 15 N-allantoin (MRM 400 → 173)) and 13 C 15 N-allantoin concentration. Sample dry weight and extraction volume were taken into consideration when calculating the final allantoin concentration.

Casartelli A., Melino V.J., Baumann U., Riboni M., Suchecki R., Jayasinghe N.S., Mendis H., Watanabe M., Erban A., Zuther E., Hoefgen R., Roessner U., Okamoto M, & Heuer S. (2019). Opposite fates of the purine metabolite allantoin under water and nitrogen limitations in bread wheat. Plant molecular biology, 99(4-5).

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