Multi-dimensional Co-separation Analysis Reveals Protein-Protein Interactions Defining Plasma Lipoprotein Subspecies

The distribution of circulating lipoprotein particles affects the risk for cardiovascular disease (CVD) in humans. Lipoproteins are historically defined by their density, with low-density lipoproteins positively and high-density lipoproteins (HDLs) negatively associated with CVD risk in large populations. However, these broad definitions tend to obscure the remarkable heterogeneity within each class. Evidence indicates that each class is composed of physically (size, density, charge) and compositionally (protein and lipid) distinct subclasses exhibiting unique functionalities and differing effects on disease. HDLs in particular contain upward of 85 proteins of widely varying function that are differentially distributed across a broad range of particle diameters. We hypothesized that the plasma lipoproteins, particularly HDL, represent a continuum of phospholipid platforms that facilitate specific protein-protein interactions. To test this idea, we separated normal human plasma using three techniques that exploit different lipoprotein physicochemical properties (gel filtration chromatography, ionic exchange chromatography, and preparative isoelectric focusing). We then tracked the co-separation of 76 lipid-associated proteins via mass spectrometry and applied a summed correlation analysis to identify protein pairs that may co-reside on individual lipoproteins. The analysis produced 2701 pairing scores, with the top hits representing previously known protein-protein interactions as well as numerous unknown pairings. A network analysis revealed clusters of proteins with related functions, particularly lipid transport and complement regulation. The specific co-separation of protein pairs or clusters suggests the existence of stable lipoprotein subspecies that may carry out distinct functions. Further characterization of the composition and function of these subspecies may point to better targeted therapeutics aimed at CVD or other diseases. Molecular & Cellular Proteomics 12: 10.1074/mcp.M113.028134, 3123-3134, 2013.