Systems proteomics for translational network medicine.

U niversal principles underlying network science and their ever-increasing applications in biomedicine underscore the unprecedented capacity of systems biology–based strategies to synthesize and resolve massive high-throughput generated data sets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multimodal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment, and complex network analysis. Proteomics encompasses diverse methods by which to study proteins, their abundance, structure, posttranslational modifications , and physical or functional interacting partners to map the proteome, the protein complement of a genome. Although such methods can be applied to individual proteins , proteomics facilitates large-scale analysis of complete proteomes or targeted subproteomes (Table 1). Moreover, proteomics enables comparisons between distinct conditions/ states, from defined biological sources, across discrete time-lines. In general, a proteomic cartography pipeline involves sample acquisition, followed by protein isolation, separation, resolution, and identification (Figure). Along this continuum, each successive module harbors a multistep process, whereby proteomic methodologies can be implemented. Once proteins are isolated from the source of interest, 2 major separation strategies have evolved to address proteome complexity. Traditional gel-based approaches, particularly 2-dimensional gel electrophoresis involving isoelectric focusing followed orthogonally by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, were the earliest methods adopted for protein separation and resolution, comparative assessment of relative abundance, and initial reduction of protein complexity before mass spectrometry (MS). Although 2-dimensional gel electrophoresis remains common, the advent of quantitative MS techniques has led to increased application of various gel-based and gel-free alternatives, whereby protein or peptide complexity is addressed by separation and resolution before or in conjunction with MS, whereas quantification is subsequently measured from MS precursor or fragment ion spectra. Choice of separation strategy is influenced by study objectives and resources, often guided by advantages and limitations to each approach. Quantitative MS methods tend to be less time-and …