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Trap columm

Manufactured by Waters Corporation
Sourced in United States

The Trap Column is a specialized laboratory equipment designed for sample preparation and purification. It serves as a solid-phase extraction (SPE) device, allowing for the selective isolation and concentration of target analytes from complex matrices. The Trap Column utilizes various sorbent materials to retain and separate specific compounds of interest, facilitating their subsequent analysis or further processing. This device provides a versatile and efficient solution for sample clean-up and analyte enrichment in various analytical workflows.

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2 protocols using trap columm

1

Label-free Proteomic Analysis Pipeline

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Label-free proteomic analysis was performed in a nanoACQUITY UPLC system (Waters, Milford, MA) coupled to a Xevo Q-TOF G2 mass spectrometer (Waters, Milford, MA), as described elsewhere (Lobo, Leite et al. 2015). The nanoACQUITY UPLC system is equipped with a Trap Columm (100Å, 5 µm, 180 µm × 200 mm) and a HSS T3 M-Class type column (analytical column 75 μm × 150 mm; 1.8 μm) (Waters, Milford, MA). ProteinLynx GlobalServer software (PLGS) version 3.03 (Waters, Milford, MA) was used to process and search the LC-MSE continuum data.
Peptides identification and difference in expression among the groups was obtained using the Protein Lynx Global Server (PLGS) software (version 3.03, Waters Co., UK) as described elsewhere (Lima Leite, Gualiume Vaz Madureira Lobo et al. 2014 (link)). The procedures and bioinformatics analysis were performed as described previously (Dionizio, Melo et al. 2018, Dionizio, Melo et al. 2020 ).
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2

Proteomic Analysis of Biological Samples

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The label-free proteomic analysis was performed in a nanoACQUITY UPLC system (Waters, Milford, MA, USA) coupled to a Xevo Q-TOF G2 mass spectrometer (Waters, Milford, MA, USA). The nanoACQUITY UPLC system was equipped with a Trap Columm (100 Å, 5 μm, 180 μm × 200 mm) and a HSS T3 M-Class type column (analytical column 75 μm × 150 mm; 1.8 μm) (Waters, Milford, MA, USA). The reading and identification of peptides was performed using the ProteinLynx GlobalServer software (PLGS) version 3.03 (Waters, Milford, MA, USA), as previously described [63 (link)]. The PLGS software, applying the Monte-Carlo algorithm, was used to determine the difference in protein expression between the groups, considering p < 0.05 for downregulated proteins and 1 − p > 0.95 for upregulated proteins. The identification of proteins was performed by downloading UniProt databases. Then, bioinformatics analyses were performed using Cytoscape® 3.6 (Java®) with the ClusterMarker plugin for the PPI network, and for the determination of the biological process groups based on Gene Ontology annotations, we used the ClueGO plugin [64 (link)].
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