Excalibur software

Manufactured by Thermo Fisher Scientific

Sourced in United States

Excalibur software is a data analysis tool designed for use with Thermo Fisher Scientific's mass spectrometry instruments. It provides a platform for processing, visualizing, and interpreting data generated by these instruments.

Automatically generated - may contain errors

Lab products found in correlation

Close spelling variants of this product

Excalibur

9 protocols using excalibur software

High-Resolution Electrospray Tandem Mass Spectrometry

Check if the same lab product or an alternative is used in the 5 most similar protocols

The high-resolution electrospray experiments were carried out using the Exploris 120 high-resolution mass spectrometer (Thermo Fisher Scientific, San José, CA, USA) equipped with heated electrospray ionization (H-ESI II) probe and an Orbitrap analyzer; the mass spectrometer was hyphenated with a Vanquish system consisting of HPLC pump and autosampler (Thermo Fisher Scientific, San José, CA, USA). Solutions coming from the purified fractions were injected into the HPLC-HR-ESI-MS system using the following conditions: spray voltage: 3.5 kV, (−4.0 kV in negative mode); sheath gas, aux gas and sweep gas 50, 10, 1 a.u., respectively; ion transfer tube temperature: 310 °C; vaporizer temperature 320 °C; the scan range was set in the range 500–1000 m/z, while the RF lens was set to 70% of the maximum value and the orbitrap resolution was set 60,000. MS² experiments were performed in data-dependent mode targeting the exact masses of protonated molecule [M + H]⁺ (m/z 741.2240) and deprotonated molecule [M − H]⁻ (m/z 739.2086) at 60,000 resolution. The system was calibrated externally to a maximum error of 2 ppm. The scan range was automatically set, while the collision energy was set to 10% and 30% of the maximum value in positive and negative mode, respectively. The molecular formulae were evaluated by Excalibur software (Thermo Fisher Scientific, San José, CA, USA).

Bartella L., Mazzotti F., Talarico I.R., De Luca G., Santoro I., Prejanò M., Riccioni C., Marino T, & Di Donna L. (2022). Structural Characterization of Peripolin and Study of Antioxidant Activity of HMG Flavonoids from Bergamot Fruit. Antioxidants, 11(10), 1847.

+ Open protocol

+ Expand

Cellular Metabolic Assessment via MTS and Seahorse

Check if the same lab product or an alternative is used in the 5 most similar protocols

Oxidative capacity was measured via the the MTS assay after 2h incubation (Promega). To measure basal oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) 80,000 cells/well were incubated for 24 h at 37°C in 5% CO₂ with XF assay media. To establish OCR and ECAR values, four readings were acquired per experiment (Seahorse Bioscience). Culture media pH was measured using a pH meter (Hanna instrument). For lactate measurements, lactate was extracted from the media after 5 days culture and TSQ Vantage mass spectrometer (Thermo). The parental ion mass followed on a negative mode was 89.0244 Da. For quantification extracted ions chromatograms for the parental ion were obtained and the area under the curve was measured using Excalibur software (version 2, Thermo Fisher Scientific).

Dermit M., Casado P., Rajeeve V., Wilkes E.H., Foxler D.E., Campbell H., Critchlow S., Sharp T.V., Gribben J.G., Unwin R, & Cutillas P.R. (2016). Oxidative stress downstream of mTORC1 but not AKT causes a proliferative defect in cancer cells resistant to PI3K inhibition. Oncogene, 36(19), 2762-2774.

+ Open protocol

+ Expand

Preprocessing for Relative Quantification of LC-MS/MS Data

Check if the same lab product or an alternative is used in the 5 most similar protocols

Raw data files produced in Excalibur software (Thermo Scientific) were processed using Proteome Discoverer, version 1.3 (Thermo Scientific) to determine peptide identification; the subsequent Mascot (version 2.3; available at: http://www.matrixscience.com) output file was used for additional preprocessing and analysis (see Supplemental Methods 5a, available online). A script was written in R to complete the preprocessing, taking into account the experimental setup described (available at: http://github.com/KHP-Informatics/PRQ). We named the script Preprocessing for Relative Quantification of LC-MS/MS data (PRQ; see Supplemental Methods–PRQ, available online). PRQ (1) performs median ratio normalization [35] (link), (2) calculates ratios for each peptide, (3) derives protein level data from peptide scores, and (4) collects the protein scores across all TMT6Plexs.

Ashton N.J., Kiddle S.J., Graf J., Ward M., Baird A.L., Hye A., Westwood S., Wong K.V., Dobson R.J., Rabinovici G.D., Miller B.L., Rosen H.J., Torres A., Zhang Z., Thurfjell L., Covin A., Hehir C.T., Baker D., Bazenet C, & Lovestone S. (2015). Blood protein predictors of brain amyloid for enrichment in clinical trials?. Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring, 1(1), 48-60.

+ Open protocol

+ Expand

Protein Identification Using Excalibur and Mascot

Check if the same lab product or an alternative is used in the 5 most similar protocols

Raw data files produced in Excalibur software (Thermo Scientific) were processed using Proteome Discoverer V1.3 (Thermo Scientific) and peptide spectral matches and subsequent protein identifications were determined using Mascot (v2.3; http://www.matrixscience.com).

Westwood S., Leoni E., Hye A., Lynham S., Khondoker M.R., Ashton N.J., Kiddle S.J., Baird A.L., Sainz-Fuertes R., Leung R., Graf J., Hehir C.T., Baker D., Cereda C., Bazenet C., Ward M., Thambisetty M, & Lovestone S. (2016). Blood-Based Biomarker Candidates of Cerebral Amyloid Using PiB PET in Non-Demented Elderly. Journal of Alzheimer's disease : JAD, 52(2), 561-572.

+ Open protocol

+ Expand

Oxidative Capacity Measurement Protocol

Check if the same lab product or an alternative is used in the 5 most similar protocols

Oxidative capacity was measured via the MTS assay after 2 h of incubation (Promega, Madison, WI, USA). To measure basal OCR and ECAR, 80 000 cells per well were incubated for 24 h at 37 °C in 5% CO₂ with XF assay media (Agilent technologies, Santa Clara, CA, USA). To establish OCR and ECAR values, four readings were acquired per experiment (Seahorse Bioscience, Santa Clara, CA, USA). Culture media pH was measured using a pH meter (Hanna Instrument). For lactate measurements, lactate was extracted from the media after 5 days of culture and subsequently analyzed by TSQ Vantage mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). The parental ion mass followed on a negative mode was 89.0244 Da. For quantification extracted ions chromatograms for the parental ion were obtained and the area under the curve was measured using Excalibur software (version 2, Thermo Fisher Scientific).

+ Open protocol

+ Expand

HPLC Analysis of Phenolic Compounds

Check if the same lab product or an alternative is used in the 5 most similar protocols

Phenolic compounds were analysed on an HPLC system (Thermo Finnigan Surveyor, Thermo Scientific, San Jose, CA, USA) equipped with a DAD detector set (280, 350, and 530 nm) following the procedure of Mikulic-Petkovsek et al. [61 (link)]. A Gemini C18 (Phenomenex, Torrance, CA, USA) column (150 × 4.6 mm i.d., 3 μm) was used at 25 °C. The samples were eluted with aqueous 0.1% formic acid and 3% acetonitrile in double-distilled water (A) and 0.1% formic acid/3% double-distilled water in acetonitrile (B) according to linear gradients reported by Wang et al. [63 (link)]. The Excalibur software was used for spectral data analyses (Thermo Fisher Scientific, Waltham, MA, USA). All phenolic compounds were identified using a mass spectrometer Thermo Finnigan LCQ Deca XP Mass (Thermo Fisher Scientific, Waltham, MA, USA) with an electrospray interface (ESI) operating in negative and positive ion modes, performing analyses under the same conditions as reported by Mikulic-Petkovsek et al. [64 (link)]. Identification of the phenolic compounds was established based on their retention times and their PDA spectra in comparison with standard phenolics and based on fragmentation patterns in different MSn modes compared with literature data. Contents of phenolics were expressed in mg/g dry weight (DW) of plant material. All analyses were performed in triplicate.

Poljuha D., Sladonja B., Šola I., Šenica M., Uzelac M., Veberič R., Hudina M., Famuyide I.M., Eloff J.N, & Mikulic-Petkovsek M. (2022). LC–DAD–MS Phenolic Characterisation of Six Invasive Plant Species in Croatia and Determination of Their Antimicrobial and Cytotoxic Activity. Plants, 11(5), 596.

+ Open protocol

+ Expand

Metabolomics Molecular Networking Analysis

Cited 1 time

Check if the same lab product or an alternative is used in the 5 most similar protocols

MS and MS/MS raw data obtained via the Excalibur Software (Thermo) were converted to a 32-bit mzXML file using MSconvert software (Proteo Wizard toolkit [20 (link)]). mzXML files were subjected to the Global Natural Product Social Molecular Networking (GNPS) site (https://gnps.ucsd.edu) as described in [21 (link)]. For the parent MS, the mass tolerance was set to 0.01 Da and for the MS/MS fragment ions, the mass tolerance was set to 0.5 Da, while the minimum cosine score was set to 0.7. The data were clustered using MSCluster with a minimum cluster size of four spectra. The spectra in the network were also searched against GNPS spectral libraries. A minimum score of 0.5 was set for spectral library search, with at least two fragment peaks matching. Cytoscape 3.7.1 was used for visualization of the generated molecular networks [22 (link),23 (link)]. The edge thickness was set to represent the cosine score, with thicker lines indicating higher similarity between nodes. The Molecular Networking job in GNPS can be found at https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=84ea45db68814c94a3b2bad9c26dd807.

Martinet L., Naômé A., Baiwir D., De Pauw E., Mazzucchelli G, & Rigali S. (2020). On the Risks of Phylogeny-Based Strain Prioritization for Drug Discovery: Streptomyces lunaelactis as a Case Study. Biomolecules, 10(7), 1027.

+ Open protocol

+ Expand

HPLC-MS/MS Analytical Protocol for Quantification

Check if the same lab product or an alternative is used in the 5 most similar protocols

For the analysis a Surveyor ® Autosampler Plus with a quaternary MSpump plus and degasser (ThermoFischer, Breda, The Netherlands) as a chromatographic system were used. A TSQ Quantum-Access ® triplequad mass spectrometer (ThermoFischer, Breda, the Netherlands) with an electrospray ionization interface combined with Excalibur ® software (version 2.2SP1) was used for detection and quantification.
Chromatographic separation was performed on a HyPURITY ® C 18 analytical column (50 × 2.1 mm, 3 μm, Thermo Fischer Scientific) combined with a drop-in guard (HyPURITY ® C 18 , 10 × 2.1 mm, 3 μm).

van Veelen A., van Geel R., de Beer Y., Dingemans A.M., Stolk L., Ter Heine R., de Vries F, & Croes S. (2020). Validation of an analytical method using HPLC-MS/MS to quantify osimertinib in human plasma and supplementary stability results. Biomedical chromatography : BMC, 34(4).

+ Open protocol

+ Expand

Analytical Quantification of Arbutin

Check if the same lab product or an alternative is used in the 5 most similar protocols

Excalibur software (ver. 2.1, Thermo Scientific, San Jose, CA, USA) was used for data acquisition and chromatographic data analysis. Microsoft Office Excel 2007 was used for statistical calculations. Comparison of the amount of arbutin in the samples collected on two localities (the islands of Koločep and Mali Lošinj) was performed by one-tailed paired t-test. Linear regression analysis using the least squares method was used to evaluate the calibration curve of analytes. Data are expressed as mean±SD (standard deviation of average value).

Jurica K., Karačonji I.B., Šegan S., Opsenica D.M, & Kremer D. (2015). Quantitative analysis of arbutin and hydroquinone in strawberry tree (Arbutus unedo L., Ericaceae) leaves by gas chromatography-mass spectrometry. Arhiv za higijenu rada i toksikologiju, 66(3).

+ Open protocol

+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Revolutionizing how scientists
search and build protocols!