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Compound discoverer software

Manufactured by Thermo Fisher Scientific
Sourced in United States, Germany

Compound Discoverer software is a data processing and analysis tool designed for the identification and characterization of unknown compounds in complex samples. The software provides automated peak detection, chromatographic deconvolution, and database-assisted identification of compounds.

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51 protocols using compound discoverer software

1

Serum Metabolite Profiling by LC-MS

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Thawed serum samples were extracted with methanol, mixed with dichlorophenylalanine, and then centrifuged. The resulting supernatant was transferred to a liquid phase bottle for testing. The analyses were performed using previously described analysis platforms, chromatographic columns, and chromatographic separation conditions (Ma et al., 2019 (link)). Compound Discoverer software (Thermo Fisher Scientific, Waltham, MA, United States) was used to extract and preprocess data from the instrument, and obtain information such as the retention time, molecular weight, sample name, and peak intensity. SIMCA-P 11 was used to analyze and plot principal component analysis (PCA), Partial Least Squares Discrimination Analysis (PLS-DA), and VIP values. The retention time and molecular weight data were compared with entries in the Human Metabolome Database (HMDB) to determine the metabolite composition of the serum samples.
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2

Metabolomic Analysis of Food Waste Fermentation

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To conduct metabolomic analyses, the fermentation products of food waste were
first pretreated with methanol. A Waters LC-MS system (Waters, UPLC; Thermo, Q
Exactive) and Acquity UPLC HSS T3 columns (2.1 × 100 mm 1.8 μm) (Waters,
Milford, MA, USA) were used for separation. The Compound Discoverer software
(Thermo company) was used to extract and preprocess the LC/MS detection data and
normalization. The results were exported as a matrix containing information such
as retention time (RT, Retention time), molecular weight (CompMW), observation
volume (sample name), number of extractable substances (ID), and peak intensity.
For quality assessment, the online human metabolite database (http://www.hmdb.ca/) was used to identify the detected
metabolites. Six replicates were analyzed for each group for detection and
analysis.
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3

Profiling SOL Extract Compounds

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The main compounds of SOL extracts were analyzed using a Vanquish UPLC system coupled with a Q ExactiveTM HF-X Hybrid Quadrupole-OrbitrapTM Mass Spectrometer (UHPLC-HRMS; Thermo Fisher Scientific). The mass spectrometer was operated in negative or positive ion mode. LC separation was done on an ACQUITY UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm) using a gradient of solvent A (10 mM ammonium formate, acetonitrile:water = 95:5, and 0.1% formic acid) and solvent B (10 mM ammonium formate, acetonitrile:water = 50:50, and 0.1% formic acid) in positive ion mode, and solvent A (10 mM ammonium acetate, acetonitrile:water = 95:5, and pH = 8) and solvent B (10 mM ammonium acetate, acetonitrile:water = 50:50, and pH = 8) in negative ion mode. The flow rate was 0.3 mL/min, the injection volume was 5 μL, and the column temperature was 25°C. In MS acquisition, the instrument was set to acquire the m/z range of over 70–1,050 with an MS resolution of 60,000. Raw data were collected by mass spectrometry, peak extraction, and retention time using the compound discoverer software (Thermo Fisher Scientific).
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4

UHPLC-HRMS Data Analysis Protocol

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UHPLC-HRMS raw data were acquired using
Xcalibur software (version 3.0 Thermo Fisher Scientific,Waltam, MA);
peaks alignment, extraction blanks subtraction, and features extraction
were performed using Compound Discoverer software (version 2.1 Thermo
Fisher Scientific,Waltam, MA) directly connected to Chemspider and m/z CLOUD databases and able to perform
in silico fragmentations; the mass range inspected was between 100
and 1000 m/z from 0.5 to 11 min
of the chromatographic runs.
The values of the critical parameters
for features extractions and identification are the same as described
in a previous work.32 (link)
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5

Liquid Chromatography-Mass Spectrometry Protocol

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Liquid chromatography-mass spectrometry analysis was carried on LC-MS (Thermo, Ultimate 3000LC, Q Exactive) platform. The parameter for both ESI+ and ESI− ion mode is listed below Heater Temp 300°C; Sheath Gas Flow rate, 45arb; Aux Gas Flow Rate, 15 arbs; Sweep Gas Flow Rate, 1arb; spray voltage, 3.0KV; Capillary Temp, 350°C; S-Lens RF Level, 30%. The data was performed with feature extraction and preprocessed with Compound Discoverer software (Thermo). Two thousand fifteen features at (ESI+) ion mode and 1,601 features at (ESI−) ion mode in this experiment, the data after editing were performed Multivariate Analysis (MVA) using SIMCA-P software (Umetrics AB, Umea, Sweden).
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6

UHPLC-MS/MS Metabolite Identification

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The LC-MS instrumentation consisted of a Thermo LTQ Orbitrap Velos mass spectrometer equipped with a FTMS analyzer (Thermo Finnegan, Waltham, MA) coupled with a Waters Acquity Ultra Performance Liquid Chromatography system (Milford, MA). A Zorbax Eclipse XDB-C18 column (4.6 X 250 mm) (Agilent, Santa Clara) was used with a flow rate of 1 mL/min. Mobile phases A: 0.1% formic acid in water and B: 0.1% formic acid in acetonitrile was used with an initial composition of 98:2 A:B held for 2 min followed by a linear gradient to 65:35 A:B over 33 min, and to 10:90 A:B over 9 min. The mass spectrometer was operated in positive ion mode or negative ion mode in a data-dependent fashion. The instrument resolution and the mass range were 30,000 and 100–700 amu, respectively. MS/MS spectra were acquired by collection of the top 6 spectra in a data dependent mode. Data analysis was conducted with Compound Discoverer software (Thermo Scientific, San Jose, CA). Metabolites were identified based on the exact mass, isotope ratio, and if available, MS/MS spectra.
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7

Metabolomic Analysis of Differentially Expressed Metabolites

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Peak alignment and extraction were performed using Compound Discoverer software (Thermo Fisher Scientific, Inc.). An unsupervised model of principal component analysis (PCA) was used to assess the overall trend of segregation between these samples. A supervised model of orthogonal projections to latent structures-discriminate analysis (OPLS-DA) was used to screen for significantly different metabolites between the groups. In order to improve the analysis, the variable importance in the projection (VIP) was obtained. VIP values >1 were first selected as changed metabolites. In addition, at a critical P-value of 0.05, these selected metabolites were further verified using two sided student's t-test. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the recognition ability of each metabolite marker. The pathways of metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www.genome.jp/kegg/) and MetaboAnalyst (http://www.metaboanalyst.ca/) (18 (link),19 (link)). P<0.05 was considered to indicate a statistically significant difference.
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8

UHPLC-MS/MS Metabolite Identification

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The LC-MS instrumentation consisted of a Thermo LTQ Orbitrap Velos mass spectrometer equipped with a FTMS analyzer (Thermo Finnegan, Waltham, MA) coupled with a Waters Acquity Ultra Performance Liquid Chromatography system (Milford, MA). A Zorbax Eclipse XDB-C18 column (4.6 X 250 mm) (Agilent, Santa Clara) was used with a flow rate of 1 mL/min. Mobile phases A: 0.1% formic acid in water and B: 0.1% formic acid in acetonitrile was used with an initial composition of 98:2 A:B held for 2 min followed by a linear gradient to 65:35 A:B over 33 min, and to 10:90 A:B over 9 min. The mass spectrometer was operated in positive ion mode or negative ion mode in a data-dependent fashion. The instrument resolution and the mass range were 30,000 and 100–700 amu, respectively. MS/MS spectra were acquired by collection of the top 6 spectra in a data dependent mode. Data analysis was conducted with Compound Discoverer software (Thermo Scientific, San Jose, CA). Metabolites were identified based on the exact mass, isotope ratio, and if available, MS/MS spectra.
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9

Metabolite Profiling by LC-MS

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The samples were thawed at room temperature, 100 μL of them was then transferred into Centrifuge Tubes (1.5 mL) by pipette. All samples were extracted with 300 μL of methanol, and 10 μL of internal standard (3 mg/mL, DL-o-Chlorophenylalanine) was added. The samples were then ultra-sonicated at 4 K Hz on ice bath for 30 min. The samples were vortexes for 30 s, and centrifuged at 12,000 rpm and 4°C for 15 min. Two hundred microliter of supernatant was transferred to vial for LC-MS analysis. Analysis platform: LC-MS (Thermo, Ultimate 3000LC, Orbitrap Elite) Column: Waters ACQUITYUPLC HSS T3column (2.1 mm × 100 mm, 1.8 μm) Chromatographic separation conditions: Column temperature: 40°C; Flow rate: 0.3 mL/min; Mobile phase A: water + 0.1% formic acid; Mobile phase B: acetonitrile + 0.1% formic acid; Injection volume: 4 μL; Automatic injector temperature: 4°C. The data was performed feature extraction and preprocessed with Compound Discoverer software (Thermo), and then normalized and edited into two-dimensional data matrix by excel 2010 software, including Retention time(RT), Compound Molecular Weight (comp MW), Observations (samples) and peak intensity.
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10

Bioactive Profiling of Cinnamon Extract

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The bioactive molecule profile of cinnamon extract before and after digestion and the methodology utilised for the analyses were reported in a previous paper [9 (link)]. Briefly, a Thermo Vanquish UHPLC system coupled with a Thermo Orbitrap Exploris 120 mass spectrometer and a Vanquish Diode Array Detector (Thermo Scientific, Rodano, Italy) was used to identify the target bioactive molecules. The chromatographic separation was carried out on a Luna Omega Polar C18 (150 mm × 2.1 mm, 3 µm) (Phenomenex, Castelmaggiore, Italy). Phenolic compounds were identified based on the corresponding spectral characteristics (UV and MS/MS spectra), accurate molecular mass, characteristic MS fragmentation pattern, and library comparison in a semi-automatic way through Compound Discoverer Software (2.1, Thermo Scientific, Rodano, Italy). A semi-quantification was carried out to reveal the changes in the compound composition of the cinnamon extract before and after digestion. All compounds were quantified in duplicate at 280 nm by external calibration lines, dividing them into two major groups according to their structural similarity: trans-cinnamic acid or catechin. The data are reported in Pagliari et al., 2023 [9 (link)].
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