Parallel Channels-Multidimensional Protein Identification Technology

Differential Precipitation of Proteins: A Simple Protein Fractionation Strategy to Gain Biological Insights with Proteomics

Differential precipitation of proteins (DiffPOP) is a simple technique for fractionating complex protein mixtures. Using stepwise addition of acidified methanol, ten distinct subsets of proteins can be selectively precipitated by centrifugation and identified by mass spectrometry-based proteomics. We have previously shown that the ability of a protein to resist precipitation can be altered by drug binding, which enabled us to identify a novel drug-target interaction. Here, we show that the addition of DiffPOP to a standard LC-MS proteomics workflow results in a three-dimensional separation of peptides that increases protein coverage and peptide identifications. Importantly, DiffPOP reveals solubility differences between proteoforms, potentially providing valuable insights that are typically lost in bottom-up proteomics.

Technological development of multidimensional liquid chromatography-mass spectrometry in proteome research

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for high-throughput proteomic research. Limited by the peak capacity, the separation performance of conventional single-dimensional LC hampers the development of proteomics. Combining different separation modes orthogonally, multidimensional liquid chromatography (MDLC) with high peak capacity was developed to address this challenge. MDLC has evolved rapidly since its establishment, and the progress of proteomics has been greatly facilitated by the advent of novel MDLC-MS-based methods. In this paper, we will review the advances of MDLC-MS-based methodologies and technologies in proteomics studies, from different perspectives including novel application scenarios and proteomic targets, automation, miniaturization, and the improvement of the classic methods in recent years. In addition, attempts regarding new MDLC-MS models are also mentioned together with the outlook of MDLC-MS-based proteomics methods.