All-by-all discovery of conserved protein complexes by deep proteome fractionation

Stable assemblies of proteins, known as protein complexes, execute a large fraction of cellular processes required to sustain life. A functional and mechanistic understanding of these assemblies will provide a more comprehensive understanding of an organisms genes and elucidate a more complete picture of cellular processes, particularly those involved in development, aging and disease. While recent progress has mapped protein complexes in budding yeast and some bacteria, efforts in animals are restricted to subsets of the proteome, leaving most animal protein complexes undetermined. Co-fractionation offers compelling efficiency gains in identifying pairwise protein interactions and complexes, but it requires significant computational efforts to fully exploit. In this work, I describe the computational methods and infrastructure I developed to identify conserved protein interactions and complexes from a massive set of mass spectrometry data from nine species and the computational and biological analysis I performed with my collaborators. These efforts include building a mostly automated pipeline to process and integrate large quantities of mass spectrometry data from multiple species and developing improved methods to predict co-complex interactions and cluster them into complexes. The conserved animal complex map produced using this pipeline and methodology has already yielded dividends in supporting biological discoveries. Scaling the approach more broadly will enable rapid mapping of the previously uncharted interactomes in any chosen species.Cellular and Molecular Biolog

Vanitas

Bachelor of Fine Arts (BFA)Bachelor of Fine ArtsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/177118/1/Borgeson-Elizabeth_CreativePortfolioFinal_2.pd

Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes

Abstract Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently, there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing > 4,600 total complexes, > 7,700 proteins, and > 56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k‐cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations, and the map overall shows improved coverage of many disease‐associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease

Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes

Abstract Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently, there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing > 4,600 total complexes, > 7,700 proteins, and > 56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k‐cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations, and the map overall shows improved coverage of many disease‐associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease

Proteome-wide dataset supporting the study of ancient metazoan macromolecular complexes

Our analysis examines the conservation of multiprotein complexes among metazoa through use of high resolution biochemical fractionation and precision mass spectrometry applied to soluble cell extracts from 5 representative model organisms Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Strongylocentrotus purpuratus, and Homo sapiens. The interaction network obtained from the data was validated globally in 4 distant species (Xenopus laevis, Nematostella vectensis, Dictyostelium discoideum, Saccharomyces cerevisiae) and locally by targeted affinity-purification experiments. Here we provide details of our massive set of supporting biochemical fractionation data available via ProteomeXchange (http://www.ebi.ac.uk/pride/archive/projects/PXD002319-http://www.ebi.ac.uk/pride/archive/projects/PXD002328), PPIs via BioGRID (185267); and interaction network projections via (http://metazoa.med.utoronto.ca) made fully accessible to allow further exploration. The datasets here are related to the research article on metazoan macromolecular complexes in Nature [1]. Keywords: Proteomics, Metazoa, Protein complexes, Biochemical, Fractionatio