Xcalibur 4

Manufactured by Thermo Fisher Scientific

Sourced in United States, Germany

Xcalibur 4.0 is a comprehensive software platform for data acquisition, processing, and management in mass spectrometry-based applications. It provides a unified interface for instrument control, data analysis, and reporting.

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222 protocols using xcalibur 4

Mass Spectrometric Analysis of Compounds

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Mass spectrometric
data were acquired using an LTQ Velos Pro linear ion trap mass spectrometer
(Thermo Scientific) equipped with a heated ESI probe coupled in-line
to the RP-UHPLC system. Nitrogen was used both as sheath gas (47 arbitrary
units) and auxiliary gas (11 arbitrary units). Data were collected
in negative ionization mode over the m/z range 150–1500 for untargeted analysis and 300–1500
for targeted analysis of higher molecular weight compounds. Data-dependent
MSⁿ analyses were performed by collision-induced
dissociation (CID) with a normalized collision energy of 35%. MSⁿ fragmentation was performed on the most intense
product ion in the MSⁿ^–1 spectrum. Dynamic exclusion with a repeat count of 3, repeat duration
of 5 s, and an exclusion duration of 5 s was used to obtain MSⁿ spectra of multiple different ions present
in full MS at the same time. Most settings were optimized by automatic
tuning using LTQ Tune Plus 4.2 in Xcalibur 4.2 (Thermo Scientific).
The ion-transfer tube temperature was 350 °C, the source heater
temperature was 408 °C, and the source voltage was 4.0 kV. Data
were processed using Xcalibur 4.2 (Thermo Scientific).

Tan J., de Bruijn W.J., van Zadelhoff A., Lin Z, & Vincken J.P. (2020). Browning of Epicatechin (EC) and Epigallocatechin (EGC) by Auto-Oxidation. Journal of Agricultural and Food Chemistry, 68(47), 13879-13887.

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Metabolite Identification by UHPLC-MS

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Metabolite identification was performed using a Vanquish ultra-high-performance liquid chromatography (UHPLC) system coupled with a Q Exactive Plus mass spectrometer equipped with an electrospray ionization (ESI) source (ThermoFisher, Waltham, USA). Data acquisition was performed via Xcalibur 4.2 software (ThermoFisher, Waltham, USA), and data analysis was conducted by using Xcalibur 4.2 and Compound Discoverer 3.2.0 software (ThermoFisher, Waltham, USA).

Zhou A., Wang Z., Diao X, & Zhong D. (2023). Characterization of in-vivo human metabolites of the oral nucleoside anti-COVID-19 drug VV116 using UHPLC-Orbitrap-MS. Journal of Pharmaceutical and Biomedical Analysis, 228, 115340.

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Mass Spectrometry Data Analysis

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Raw data were first analysed manually using Xcalibur 4.1 (Thermo Fisher Scientific). The relative abundance of each species in a real-time measurement was quantified using Lig2Apo, a simple jupyter notebook. A folder of text files (format m/z versus intensity) was exported from Xcalibur 4.1 (Thermo Fischer Scientific) and two series of m/z values were defined corresponding to the molecular species of interest. The program then read all text files and calculated the relative intensity of the series and the intensity ratio of two species (see Code availability). The zero charge spectra presented in Fig. 2 were analysed by Unidec v.2.7.3^{34 (link)}. The rate constants were analysed by OriginPro 2020 SR1 9.7.0.188.

Chen S., Getter T., Salom D., Wu D., Quetschlich D., Chorev D.S., Palczewski K, & Robinson C.V. (2022). Capturing a rhodopsin receptor signalling cascade across a native membrane. Nature, 604(7905), 384-390.

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Metabolomic Analysis of Biological Samples

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First, the raw data are acquired by Xcalibur 4.1 software (Thermo Fisher Scientific, Waltham, MA, USA), and initial data processing, including peak detection and peak alignment, was performed in Compound Discoverer 3.1 software (Thermo Fisher Scientific, Waltham, MA, USA) as described previously [39 (link)]. Then, the partial least-squares-latent structure discriminates analysis (PLS-DA) models were built for multivariate statistical analysis using SIMCA-P 13.0 (Umetrics AB, Umea, Sweden) and metabolites with variable importance in the project (VIP) values of more than 1 were selected as differential metabolites [40 (link)]. Next, univariate analysis was performed, and the biologically significant metabolites were identified according to the pathway mapping results in Compound Discoverer 3.1 by referring to local libraries and online databases, among which the online data sources of ChemSpider were composed of the Human Metabolome Database, Kyoto Encyclopedia of Genes and Genomes, and Biocyc. Moreover, the mzCloud library was also used for spectral searching. Finally, the hierarchical cluster analysis of biological differential metabolites was conducted in Cluster 3.0 software [41 (link)].

Wu L., Han Y., Zheng Z., Zhu S., Chen J., Yao Y., Yue S., Teufel A., Weng H., Li L, & Wang B. (2021). Obeticholic Acid Inhibits Anxiety via Alleviating Gut Microbiota-Mediated Microglia Accumulation in the Brain of High-Fat High-Sugar Diet Mice. Nutrients, 13(3), 940.

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Mass Spectrometric Characterization of Compounds

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Mass spectra were acquired
on a QExactive Orbitrap system (Thermo Fischer Scientific) with a
modified matrix-assisted laser desorption/ionization/ESI injector
(Spectroglyph, LLC), operated in the ESI mode at a 140,000 resolution
both for MS and MS/MS measurements. Solutions of target compounds
in a methanol–water mixture (1:1) were infused with the flow
rate of 1 μL·min^–1 and the spray voltage
of 3 kV. Precursor ions corresponding to protonated (or deuterated)
molecules and the isotope exchange reaction products were isolated
with a 0.4 Da window and fragmented with various collision energy
values ranging from 10 to 90 NCE. Nitrogen was used as the collision
gas. Also, for some compounds, an LC–MS/MS system was used
(see the Supporting Information for more
details). All spectra were preprocessed using XCalibur 4.1 software
(Thermo Fischer Scientific) to extract MS/MS spectra for all target
ions averaged by different collision energies.

Kostyukevich Y., Sosnin S., Osipenko S., Kovaleva O., Rumiantseva L., Kireev A., Zherebker A., Fedorov M, & Nikolaev E.N. (2022). PyFragMS—A Web Tool for the Investigation of the Collision-Induced Fragmentation Pathways. ACS Omega, 7(11), 9710-9719.

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Metabolomic Analysis of Fecal Samples

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Fecal samples were prepared and examined according to previously established methods.^{60 (link)} The sample was detected by a Dionex UltiMate 3000 RS ultraperformance liquid chromatography (UPLC) system. A Hypersil Gold C−18 column (2.1 × 100 mm, 1.9 µm, Thermo Fisher Scientific, USA) was used in both ESI⁺ and ESI⁻ modes. Mass spectrometric analysis was detected by Q Exactive HF-X mass spectrometry (MS) with a heated-ESI-II (HESI-II) ion source (Thermo Scientific, USA). Raw data were collected by Xcalibur™ 4.1 software and processed by Compound Discoverer™ 3.1 software (Thermo Fisher Scientific, USA). The hierarchical cluster analysis of metabolites was based on the log2 fold change of the normalized area in each sample divided by the group area of the NC and was conducted using Cluster 3.0 software.

Han Y., Ling Q., Wu L., Wang X., Wang Z., Chen J., Zheng Z., Zhou Z., Jia L., Li L, & Wang B. (2023). Akkermansia muciniphila inhibits nonalcoholic steatohepatitis by orchestrating TLR2-activated γδT17 cell and macrophage polarization. Gut Microbes, 15(1), 2221485.

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UHPLC-MS Analysis of Chemical Ingredients

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Chemical ingredients analysis was performed in a Vanquish UHPLC system (Thermo Fisher Scientific Inc.) with an electrospray ionization (ESI) interface. An ACQUITY UPLC^® HSS (Waters, USA) T3 column (2.1 mm × 100 mm, 1.8 μm) was applied for chromatographic analysis at 40 °C column temperature with a flow rate of 0.2 mL/min. The mobile phase was composed of water containing 0.1% formic acid (v/v, A) and acetonitrile (B), with a gradient elution as follows: 10% B at 0-2 min, 10%-95% B at 2-11 min, 95% B at 11-14 min, 95%-10% B at 14-14.1 min and 10% B at 14.1-17 min. The injection volume was 5 μL.
Mass spectrometric analysis was operated in negative and positive ionization modes and the data collecting as well as analysis were carried out using Xcalibur 4.1 software (Thermo Fisher). The parameters in the source were set as follows: sheath gas (N₂) flow rate at 30 Arb, auxiliary gas (N₂) flow rate at 10 Arb, probe heater temperature at 350 °C, capillary temperature at 320 °C, the full MS scan range at 100 to 1500 m/z with a resolution of 12,000 and the MS/dd-MS2 with a resolution of 30,000.

Yu B., Zhou M., Dong Z., Zheng H., Zhao Y., Zhou J., Zhang C., Wei F., Yu G., Liu W.J., Liu H, & Wang Y. (2023). Integrating network pharmacology and experimental validation to decipher the mechanism of the Chinese herbal prescription modified Shen-Yan-Fang-Shuai formula in treating diabetic nephropathy. Pharmaceutical Biology, 61(1), 1222-1233.

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Metabolomic Analysis of Rat Substantia Nigra

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SNc was dissected and snap-frozen on dry ice and stored at −80°C until processed. Acetonitrile/water (80:20) equilibrated to −20°C was pipetted into each sample tube in a volume of 20 μl/mg of tissue (range, 2.4 to 6.1 mg). Tissue was mechanically dissociated by pipetting up and down. Samples were frozen on dry ice and thawed six times, each time followed by pipetting up and down, and then stored at −80°C overnight. Once thawed, samples were vortexed for 1 min and then centrifuged for 30 min at 4°C at 14,000g. The supernatant was then transferred to high-performance liquid chromatography (HPLC) tubes and stored at −80°C. Subsequently, samples were analyzed by ultrahigh-performance liquid chromatography and high-resolution mass spectrometry and tandem mass spectrometry, as described previously (108 (link)). Data acquisition and analysis were carried out by Xcalibur 4.1 software and Tracefinder 4.1 software, respectively (both from Thermo Fisher Scientific). The peak area for each detected metabolite was normalized by the total ion current, which was determined by integration of all the recorded peaks within the acquisition window. Metabolomics services were performed by the Metabolomics Core Facility at Robert H. Lurie Comprehensive Cancer Center of Northwestern University.

Zampese E., Wokosin D.L., Gonzalez-Rodriguez P., Guzman J.N., Tkatch T., Kondapalli J., Surmeier W.C., D’Alessandro K.B., De Stefani D., Rizzuto R., Iino M., Molkentin J.D., Chandel N.S., Schumacker P.T, & Surmeier D.J. (2022). Ca2+ channels couple spiking to mitochondrial metabolism in substantia nigra dopaminergic neurons. Science Advances, 8(39), eabp8701.

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Proteomic Analysis of Isolated Glomeruli

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Glomeruli were isolated by dynabead perfusion from male BALB/c mice as previously described (14 (link), 72 (link)) and incubated for 24 h in RPMI-1640 containing l-glutamine and NaHCO₃, supplemented with 10% fetal bovine serum (Sigma Aldrich) before appropriate stimulation. Glomerular proteins were extracted in RIPA lysis and extraction buffer (ThermoFisher) and prepared for TMT-based mass spectrometer analysis. All spectra were acquired using an Orbitrap Fusion Lumos mass spectrometer controlled by Xcalibur 4.1 software (Thermo Scientific). The data output from Proteome Discoverer 2.1 was handled, processed, and further analyzed in Microsoft Office Excel, GraphPad Prism, Perseus, and R. Log2-transformed scaled total protein abundance data and adjusted phospho-peptide data were used for analysis. Enrichment analysis was performed with IPA (45 (link)), using all detected proteins/phosphoproteins in our TMT-MS/MS analysis as background.

Lay A.C., Barrington A.F., Hurcombe J.A., Ramnath R.D., Graham M., Lewis P.A., Wilson M.C., Heesom K.J., Butler M.J., Perrett R.M., Neal C.R., Herbert E., Mountjoy E., Atan D., Nair V., Ju W., Nelson R.G., Kretzler M., Satchell S.C., McArdle C.A., Welsh G.I, & Coward R.J. (2020). A role for NPY-NPY2R signaling in albuminuric kidney disease. Proceedings of the National Academy of Sciences of the United States of America, 117(27), 15862-15873.

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Comprehensive Characterization of CILF Chemical Constituents

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The main chemical constituents of CILF were characterized by UPLC-Q/Orbitrap HRMS, and LC separation was performed on a Hypersll GOLD C18 column (100 × 2.1 mm, 3 μm, Thermo Fisher Scientific, CA, USA). The column temperature was maintained at 30°C. The mobile phase was composed of 0.1% acetonitrile (A) and 0.1% formic acid/water (B) at a flow rate of 0.3 mL/min. The gradient elution program was as follows: 0~2 min:2% A→5% A;2~5 min:5% A→10% A;5~12 min: 10% A→16% A. The detection wavelength was set at 254 nm.
Mass spectrometry analysis was performed on a Q-Exactive Plus™ mass spectrometer (Thermo Fisher). The MS instrument was connected to UHPLC via a heated electrospray ionization (HESI) interface. The HESI source was operated in ion mode. The carrier was nitrogen, while the sheath gas and auxiliary gas pressures were MPa and 1.0 MPa, respectively. The spray voltage was 3.80 kV in positive mode and 3.00 kV in negative mode. The capillary temperature was set to 350 °C and the auxiliary heater to 200 °C. The resolution was 70,000 for full MS and 17,500 for data-dependent MS2. Compounds were detected at a mass-to-charge-ratio of 100 to 1500 m/z, and fixed collision energies were used (20, 30, 40 eV). Data were processed using Xcalibur™ 4.1 software (Thermo Fisher).

Amatjan M., Li N., He P., Zhang B., Mai X., Jiang Q., Xie H, & Shao X. (2023). A Novel Approach Based on Gut Microbiota Analysis and Network Pharmacology to Explain the Mechanisms of Action of Cichorium intybus L. Formula in the Improvement of Hyperuricemic Nephropathy in Rats. Drug Design, Development and Therapy, 17, 107-128.

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