The protein samples were in-gel digested with 10 ng/μl Glu-C. Then, the peptide samples were resuspended in loading buffer (0.03% trifluoroacetic acid, 0.1% formic acid, and 1% acetonitrile), then loaded onto a 20-cm nano-HPLC column and finally generated by a Dionex RSLCnano UPLC system (Thermo, USA). Peptides were ionized with 2.0 kV electrospray ionization voltage from a nano-ESI source on an Orbitrap Fusion mass spectrometer (Thermo, USA) [28 (link)].
Dionex rslcnano uplc system
Manufactured by Thermo Fisher Scientific
Sourced in United States
The Dionex RSLCnano UPLC system is a high-performance liquid chromatography (HPLC) instrument designed for nano-scale and capillary-scale separations. It provides precise and sensitive analysis of small sample volumes. The system is capable of operating at high pressures to enable the use of small particle size columns for improved separation efficiency and resolution.
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Lab products found in correlation
2 protocols using dionex rslcnano uplc system
1
Protein Digestion for Mass Spectrometry
2
Quantitative Proteomics Analysis of Porcine and Human Samples
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The eight fractions containing the peptides were resuspended in 0.1% formic acid (FA) before liquid chromatography mass spectrometry was performed. Six microliters of each sample were injected into a Dionex RSLC nanoUPLC system connected to an Orbitrap Fusion mass spectrometer (Thermo Scientific, Waltham, MA) equipped with an Easy Spray ion source. Liquid chromatography and mass spectrometry in TMT synchronous precursor selection MS3 mode were performed as described in a previous work [4 (link)]. With the Sequest HT database, mass spectrometry raw data were searched against the Uniprot Sus scrofa database and the Homo sapiens Uniprot database using Proteome Discoverer 2.1 as previously described [5 (link)]. A false discovery rate of 1% was used to identify proteins. The false discovery rate was calculated using the automated false discovery rate calculations of Proteome Discoverer that uses a Decoy Database search to determine the false discovery rate.
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