Improved method for the analysis of membrane proteins by mass spectrometry.

Physiol Genomics

National Center for Proteomics Research, Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA.

Published: June 2007

Membrane-bound and membrane-associated proteins are difficult to analyze by mass spectrometry, since the association with lipids impedes the isolation and solubilization of the proteins in buffers suitable for mass spectrometry and the efficient generation of positively charged peptide ions by electrospray ionization. Current methods mostly utilize detergents for the isolation of proteins from membranes. In this study, we present an improved detergent-free method for the isolation and mass spectrometric identification of membrane-bound and membrane-associated proteins. We delipidate proteins from the membrane bilayer by chloroform extraction to overcome dissolution and ionization problems during analysis. Comparison of our results to results obtained by direct tryptic digestion of insoluble membrane pellets identifies an increased number of membrane proteins, and a higher quality of the resulting mass spectral data.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2814522PMC
http://dx.doi.org/10.1152/physiolgenomics.00279.2006DOI Listing

Publication Analysis

Top Keywords

mass spectrometry
12
membrane proteins
8
membrane-bound membrane-associated
8
membrane-associated proteins
8
proteins
7
mass
5
improved method
4
method analysis
4
membrane
4
analysis membrane
4

Similar Publications

Automated High-Throughput Affinity Capture-Mass Spectrometry Platform with Data-Independent Acquisition.

J Proteome Res

January 2025

Discovery Research, AbbVie, Inc., 1 North Waukegan Rd., North Chicago, Illinois 60064, United States.

Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small-molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process have limited its use in a high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small-molecule target enrichment in the 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis.

View Article and Find Full Text PDF

Purpose: Major cardiovascular surgery imposes high physiologic stress, often causing severe organ dysfunction and poor outcomes. The underlying mechanisms remain unclear. This study investigated metabolic changes induced by major cardiovascular surgery and the potential role of identified metabolic signatures in postoperative acute kidney injury (AKI).

View Article and Find Full Text PDF

Compound-specific stable isotope analysis (CSIA) using liquid chromatography-isotope ratio mass spectrometry (LC-IRMS) is a powerful tool for determining the isotopic composition of carbon in analytes from complex mixtures. However, LC-IRMS methods are constrained to fully aqueous eluents. Previous efforts to overcome this limitation were unsuccessful, as the use of organic eluents in LC-IRMS was deemed impossible.

View Article and Find Full Text PDF

Tomato (Solanum lycopersicum L.) is an important model plant whose fleshy fruit consists of well-differentiated tissues. Recently it was shown that these tissues develop hypoxia during fruit development and ripening.

View Article and Find Full Text PDF

QuanFormer: A Transformer-Based Precise Peak Detection and Quantification Tool in LC-MS-Based Metabolomics.

Anal Chem

January 2025

State Key Laboratory of Cellular Stress Biology, Institute of Artificial Intelligence, School of Life Sciences, Faculty of Medicine and Life Sciences, National Institute for Data Science in Health and Medicine, XMU-HBN skin biomedical research center, Xiamen University, Xiamen, Fujian 361102, China.

In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reliability and reproducibility of results. To address these challenges, we developed QuanFormer, a deep learning method based on object detection designed to accurately quantify peak signals.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!