LC-MS proteomics 'improved with MRCQuant'

MRCQuant, a method of maximum ratio combining (MRC) for liquid chromatography-mass spectrometry (LC-MS) processes, raises the success of proteomics studies, according to its developers.

Writing in BMC Bioinformatics, the team from the University of Texas explain that relative isotope abundance quantification typically plays a major role in LC-MS proteomics.

But it is subject to issues during analysis, including mass drift correction, interference removal, thermal noise suppression and liquid chromatography (LC) peak boundary detection.

To overcome these, the researchers developed MRCQuant, an MRC-based method of detecting LC peak boundaries and of detecting and removing interference from the mass spectrometry part of the process.

"MRCQuant effectively addresses major issues in the relative quantification of LC-MS-based proteomics," they write.

"It provides improved performance in the quantification of low-abundance peptides."

The tests performed revealed the method capable of delivering a greater number of accurately quantified peptides, with significant improvements over representative alternative algorithms.

BMC Bioinformatics specialises in research into statistical and computational techniques for scientific analysis.