Label-free quantitative proteomics trends for protein–protein interactions

Label-free quantitative proteomics trends for protein-protein interactions.

Understanding protein interactions within the complexity of a living cell is challenging, but techniques coupling affinity purification and mass spectrometry have enabled important progress to be made in the past 15 years. As identification of protein-protein interactions is becoming easier, the quantification of the interaction dynamics is the next frontier. Several quantitative mass spectrome...

Mass Spectrometry-Based Label-Free Quantitative Proteomics

In order to study the differential protein expression in complex biological samples, strategies for rapid, highly reproducible and accurate quantification are necessary. Isotope labeling and fluorescent labeling techniques have been widely used in quantitative proteomics research. However, researchers are increasingly turning to label-free shotgun proteomics techniques for faster, cleaner, and ...

Data from quantitative label free proteomics analysis of rat spleen

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in thi...

Label-free Quantitative Proteomics Reveals Differentially Regulated Proteins Influencing Urolithiasis*

Urinary proteins have been implicated as inhibitors of kidney stone formation (urolithiasis). As a proximal fluid, prefiltered by the kidneys, urine is an attractive biofluid for proteomic analysis in urologic conditions. However, it is necessary to correct for variations in urinary concentration. In our study, individual urine samples were normalized for this variation by using a total protein...

Gel-Free Proteome Analysis Isotopic Labelling Vs. Label-Free Approaches for Quantitative Proteomics